Ancestry specific distribution of LPA Kringle IV-Type-2 genetic variants highlight associations to apo(a) copy number, glucose, and hypertension.

Background: High Lp(a) levels contribute to atherosclerotic cardiovascular disease and are tightly regulated by the LPA gene . Lp(a) levels have an inverse correlation with LPA Kringle IV Type-2 (KIV-2) copy number (CN). Black (B) and Hispanic (H) individuals exhibit higher levels of Lp(a), and rates of CVD compared to non-Hispanic Whites (NHW). Therefore, we investigated genetic variations in the LPA KIV-2 region across three ancestries and their associations with metabolic risk factors. Methods: Using published pipelines, we analyzed a multi-ethnic whole exome dataset comprising 3,817 participants from the Washington Heights and Inwood Columbia Aging Project (WHICAP): 886 [NHW (23%), 1,811 Caribbean (C) H (47%), and 1,120 B individuals (29%). Rare and common variants (alternative allele carrier frequency, CF < 0.01 or > 0.99 and 0.01 < CF < 0.99, respectively) were identified and KIV-2 CN estimated. The associations of variants and CN with history of heart disease, hypertension (HTN), stroke, lipid levels and clinical diagnosis of Alzheimer's disease (AD) was assessed. A small pilot provided in-silico validation of study findings. Results: We report 1421 variants in the LPA KIV-2 repeat region, comprising 267 exonic and 1154 intronic variants. 61.4% of the exonic variants have not been previously described. Three novel exonic variants significantly increase the risk of HTN across all ethnic groups: 4785-C/A (frequency = 78%, odds ratio [OR] = 1.45, p = 0.032), 727-T/C (frequency = 96%, OR = 2.11, p = 0.032), and 723-A/G (frequency = 96%, OR = 1.97, p = 0.038). Additionally, six intronic variants showed associations with HTN: 166-G/A, 387-G/C, 402-G/A, 4527-A/T, 4541-G/A, and 4653-A/T. One intronic variant, 412-C/T, was associated with decreased blood glucose levels (frequency = 72%, ß = -14.52, p = 0.02).Three of the associations were not affected after adjusting for LPA KIV-2 CN: 412-C/T (ß = -14.2, p = 0.03), 166-G/A (OR = 1.41, p = 0.05), and 387-G/C (OR = 1.40, p = 0.05). KIV CN itself was significantly associated with 314 variants and was negatively correlated with plasma total cholesterol levels. Conclusions: In three ancestry groups, we identify novel rare and common LPA KIV-2 region variants. We report new associations of variants with HTN and Glucose levels. These results underscore the genetic complexity of the LPA KIV-2 region in influencing cardiovascular and metabolic health, suggesting potential genetic regulation of pathways that can be studied for research and therapeutic interventions.

Resolving intra-repeat variation in medically relevant VNTRs from short-read sequencing data using the cardiovascular risk gene LPA as a model.

BACKGROUND: Variable number tandem repeats (VNTRs) are highly polymorphic DNA regions harboring many potentially disease-causing variants. However, VNTRs often appear unresolved ("dark") in variation databases due to their repetitive nature. One particularly complex and medically relevant VNTR is the KIV-2 VNTR located in the cardiovascular disease gene LPA which encompasses up to 70% of the coding sequence. RESULTS: Using the highly complex LPA gene as a model, we develop a computational approach to resolve intra-repeat variation in VNTRs from largely available short-read sequencing data. We apply the approach to six protein-coding VNTRs in 2504 samples from the 1000 Genomes Project and developed an optimized method for the LPA KIV-2 VNTR that discriminates the confounding KIV-2 subtypes upfront. This results in an F1-score improvement of up to 2.1-fold compared to previously published strategies. Finally, we analyze the LPA VNTR in > 199,000 UK Biobank samples, detecting > 700 KIV-2 mutations. This approach successfully reveals new strong Lp(a)-lowering effects for KIV-2 variants, with protective effect against coronary artery disease, and also validated previous findings based on tagging SNPs. CONCLUSIONS: Our approach paves the way for reliable variant detection in VNTRs at scale and we show that it is transferable to other dark regions, which will help unlock medical information hidden in VNTRs.

Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers.

Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present 'Imputation Server PGS', an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu.

Genetic determinants of complement activation in the general population.

Complement is a fundamental innate immune response component. Its alterations are associated with severe systemic diseases. To illuminate the complement's genetic underpinnings, we conduct genome-wide association studies of the functional activity of the classical (CP), lectin (LP), and alternative (AP) complement pathways in the Cooperative Health Research in South Tyrol study (n = 4,990). We identify seven loci, encompassing 13 independent, pathway-specific variants located in or near complement genes (CFHR4, C7, C2, MBL2) and non-complement genes (PDE3A, TNXB, ABO), explaining up to 74% of complement pathways' genetic heritability and implicating long-range haplotypes associated with LP at MBL2. Two-sample Mendelian randomization analyses, supported by transcriptome- and proteome-wide colocalization, confirm known causal pathways, establish within-complement feedback loops, and implicate causality of ABO on LP and of CFHR2 and C7 on AP. LP causally influences collectin-11 and KAAG1 levels and the risk of mouth ulcers. These results build a comprehensive resource to investigate the role of complement in human health.

Meta-GWAS on PCSK9 concentrations reveals associations of novel loci outside the PCSK9 locus in White populations.

BACKGROUND AND AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Toll-Like Receptor 3 Mediates Aortic Stenosis Through a Conserved Mechanism of Calcification.

BACKGROUND: Calcific aortic valve disease (CAVD) is characterized by a phenotypic switch of valvular interstitial cells to bone-forming cells. Toll-like receptors (TLRs) are evolutionarily conserved pattern recognition receptors at the interface between innate immunity and tissue repair. Type I interferons (IFNs) are not only crucial for an adequate antiviral response but also implicated in bone formation. We hypothesized that the accumulation of endogenous TLR3 ligands in the valvular leaflets may promote the generation of osteoblast-like cells through enhanced type I IFN signaling. METHODS: Human valvular interstitial cells isolated from aortic valves were challenged with mechanical strain or synthetic TLR3 agonists and analyzed for bone formation, gene expression profiles, and IFN signaling pathways. Different inhibitors were used to delineate the engaged signaling pathways. Moreover, we screened a variety of potential lipids and proteoglycans known to accumulate in CAVD lesions as potential TLR3 ligands. Ligand-receptor interactions were characterized by in silico modeling and verified through immunoprecipitation experiments. Biglycan (Bgn), Tlr3, and IFN-α/ß receptor alpha chain (Ifnar1)-deficient mice and a specific zebrafish model were used to study the implication of the biglycan (BGN)-TLR3-IFN axis in both CAVD and bone formation in vivo. Two large-scale cohorts (GERA [Genetic Epidemiology Research on Adult Health and Aging], n=55 192 with 3469 aortic stenosis cases; UK Biobank, n=257 231 with 2213 aortic stenosis cases) were examined for genetic variation at genes implicated in BGN-TLR3-IFN signaling associating with CAVD in humans. RESULTS: Here, we identify TLR3 as a central molecular regulator of calcification in valvular interstitial cells and unravel BGN as a new endogenous agonist of TLR3. Posttranslational BGN maturation by xylosyltransferase 1 (XYLT1) is required for TLR3 activation. Moreover, BGN induces the transdifferentiation of valvular interstitial cells into bone-forming osteoblasts through the TLR3-dependent induction of type I IFNs. It is intriguing that Bgn-/-, Tlr3-/-, and Ifnar1-/- mice are protected against CAVD and display impaired bone formation. Meta-analysis of 2 large-scale cohorts with >300 000 individuals reveals that genetic variation at loci relevant to the XYLT1-BGN-TLR3-interferon-α/ß receptor alpha chain (IFNAR) 1 pathway is associated with CAVD in humans. CONCLUSIONS: This study identifies the BGN-TLR3-IFNAR1 axis as an evolutionarily conserved pathway governing calcification of the aortic valve and reveals a potential therapeutic target to prevent CAVD.

KLKB1 and CLSTN2 are associated with HDL-mediated cholesterol efflux capacity in a genome-wide association study.

BACKGROUND AND AIMS: HDL-mediated cholesterol efflux capacity (CEC) may protect from cardiovascular disease. Thus, we aimed to identify its genetic and non-genetic determinants. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.

Development of an LC-MRM-MS-Based Candidate Reference Measurement Procedure for Standardization of Serum Apolipoprotein (a) Tests.

BACKGROUND: Medical results generated by European CE Marking for In Vitro Diagnostic or in-house tests should be traceable to higher order reference measurement systems (RMS), such as International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)-endorsed reference measurement procedures (RMPs) and reference materials. Currently, serum apolipoprotein (a) [apo(a)] is recognized as a novel risk factor for cardiovascular risk assessment and patient management. The former RMS for serum apo(a) is no longer available; consequently, an International System of Units (SI)-traceable, ideally multiplexed, and sustainable RMS for apo(a) is needed. METHODS: A mass spectrometry (MS)-based candidate RMP (cRMP) for apo(a) was developed using quantitative bottom-up proteomics targeting 3 proteotypic peptides. The method was provisionally validated according to ISO 15193 using a single human serum based calibrator traceable to the former WHO-IFCC RMS. RESULTS: The quantitation of serum apo(a) was by design independent of its size polymorphism, was linear from 3.8 to 456 nmol/L, and had a lower limit of quantitation for apo(a) of 3.8 nmol/L using peptide LFLEPTQADIALLK. Interpeptide agreement showed Pearson Rs of 0.987 and 0.984 for peptides GISSTVTGR and TPENYPNAGLTR, and method comparison indicated good correspondence (slopes 0.977, 1.033, and 1.085 for LFLEPTQADIALLK, GISSTVTGR, and TPENYPNAGLTR). Average within-laboratory imprecision of the cRMP was 8.9%, 11.9%, and 12.8% for the 3 peptides. CONCLUSIONS: A robust, antibody-independent, MS-based cRMP was developed as higher order RMP and an essential part of the apo(a) traceability chain and future RMS. The cRMP fulfils predefined analytical performance specifications, making it a promising RMP candidate in an SI-traceable MS-based RMS for apo(a).

Commutability Assessment of Candidate Reference Materials for Lipoprotein(a) by Comparison of a MS-based Candidate Reference Measurement Procedure with Immunoassays.

BACKGROUND: Elevated concentrations of lipoprotein(a) [Lp(a)] are directly related to an increased risk of cardiovascular diseases, making it a relevant biomarker for clinical risk assessment. However, the lack of global standardization of current Lp(a) measurement procedures (MPs) leads to inconsistent patient care. The International Federation for Clinical Chemistry and Laboratory Medicine working group on quantitating apolipoproteins by mass spectrometry (MS) aims to develop a next-generation SI (International system of units)-traceable reference measurement system consisting of a MS-based, peptide-calibrated reference measurement procedure (RMP) and secondary serum-based reference materials (RMs) certified for their apolipoprotein(a) [apo(a)] content. To reach measurement standardization through this new measurement system, 2 essential requirements need to be fulfilled: a sufficient correlation among the MPs and appropriate commutability of future serum-based RMs. METHODS: The correlation among the candidate RMP (cRMP) and immunoassay-based MPs was assessed by measuring a panel of 39 clinical samples (CS). In addition, the commutability of 14 different candidate RMs was investigated. RESULTS: Results of the immunoassay-based MPs and the cRMPs demonstrated good linear correlations for the CS but some significant sample-specific differences were also observed. The results of the commutability study show that RMs based on unspiked human serum pools can be commutable with CS, whereas human pools spiked with recombinant apo(a) show different behavior compared to CS. CONCLUSIONS: The results of this study show that unspiked human serum pools are the preferred candidate secondary RMs in the future SI-traceable Lp(a) Reference Measurement System.

The kringle IV type 2 domain variant 4925G>A causes the elusive association signal of the LPA pentanucleotide repeat.

Lipoprotein(a) [Lp(a)] concentrations are regulated by the LPA gene mainly via the large kringle IV-type 2 (KIV-2) copy number variation and multiple causal variants. Early studies suggested an effect of long pentanucleotide repeat (PNR) alleles (10 and 11 repeats, PNR10 and PNR11) in the LPA promoter on gene transcription and found an association with lower Lp(a). Subsequent in vitro studies showed no effects on mRNA transcription, but the association with strongly decreased Lp(a) remained consistent. We investigated the isolated and combined effect of PNR10, PNR11, and the frequent splice site variant KIV-2 4925G>A on Lp(a) concentrations in the Cooperative Health Research in the Region of Augsburg F4 study by multiple quantile regression in single-SNP and joint models. Data on Lp(a), apolipoprotein(a) Western blot isoforms, and variant genotypes were available for 2,858 individuals. We found a considerable linkage disequilibrium between KIV-2 4925G>A and the alleles PNR10 and PNR11. In single-variant analysis adjusted for age, sex, and the shorter apo(a) isoform, we determined that both PNR alleles were associated with a highly significant Lp(a) decrease (PNR10: ß = -14.43 mg/dl, 95% CI: -15.84, -13.02, P = 3.33e-84; PNR11: ß = -17.21 mg/dl, 95% CI: -20.19, -14.23, P = 4.01e-29). However, a joint model, adjusting the PNR alleles additionally for 4925G>A, abolished the effect on Lp(a) (PNR10: ß = +0.44 mg/dl, 95% CI: -1.73, 2.60, P = 0.69; PNR11: ß = -1.52 mg/dl, 95% CI: -6.05, 3.00, P = 0.51). Collectively, we conclude that the previously reported Lp(a) decrease observed in pentanucleotide alleles PNR10 or PNR11 carriers results from a linkage disequilibrium with the frequent splicing mutation KIV-2 4925G>A.

Lipoprotein(a) beyond the kringle IV repeat polymorphism: The complexity of genetic variation in the LPA gene.

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.

The effect of LPA Thr3888Pro on lipoprotein(a) and coronary artery disease is modified by the LPA KIV-2 variant 4925G>A.

BACKGROUND AND AIMS: 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. METHODS: Effects on Lp(a) concentrations were investigated by multiple quantile regression in the German Chronic Kidney Disease (GCKD) study, KORA-F3 and KORA-F4 (ntotal = 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. RESULTS: 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) (ß = -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) (ß = +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. CONCLUSIONS: 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.

Genome-Wide Characterization of a Highly Penetrant Form of Hyperlipoprotein(a)emia Associated With Genetically Elevated Cardiovascular Risk.

BACKGROUND: Lp(a) (lipoprotein [a]) is a highly atherogenic lipoprotein strongly associated with coronary artery disease (CAD). Lp(a) concentrations are chiefly determined genetically. Investigation of large pedigrees with extreme Lp(a) using modern whole-genome approaches may unravel the genetic determinants underpinning this pathological phenotype. METHODS: A large family characterized by high Lp(a) and increased CAD incidence was recruited by cascade screening. Plasma lipids, lipoproteins, and apolipoproteins concentrations, as well as the size of apo(a) isoforms, were determined enzymatically by high-resolution mass spectrometry and Western blot, respectively. Whole-exome sequencing was performed to search for rare defects in modifier genes. Genetic risk scores (GRS) for Lp(a) and CAD were calculated and their discriminative power was assessed. RESULTS: Seventeen individuals displayed extreme Lp(a) levels including 6 with CAD. Whole-exome sequencing showed no hint for genetic defects outside the LPA locus. The extreme Lp(a) phenotype segregated with the presence of a short apo(a) isoform containing 21 Kringle IV domains. This allele was characterized by the presence of three rare strongly Lp(a) increasing single nucleotide polymorphisms and a significantly increased load of oxidized phospholipids per Lp(a) particle. An Lp(a) GRS consisting of 48 single nucleotide polymorphisms that represent 2001 genome-wide significant LPA single nucleotide polymorphisms, efficiently captured the hyper-Lp(a) phenotype and discriminated affected and nonaffected individuals with great accuracy. The genome-wide GRS for CAD, encompassing 6.6 million single nucleotide polymorphisms, was very high for most family members (>97.5 percentile of the reference population), but this observation was no longer valid when the contribution of the LPA locus was omitted. CONCLUSIONS: High-Lp(a) phenotypes can be successfully captured using the Lp(a) GRS even among closely related family members. In hyper-Lp(a) individuals, LPA can be a major locus driving a very high CAD GRS. This underpins the large contribution of the LPA locus to the cardiovascular genetic risk in families.

Lipoprotein(a) and SARS-CoV-2 infections: Susceptibility to infections, ischemic heart disease and thromboembolic events.

BACKGROUND: Comorbidities including ischemic heart disease (IHD) worsen outcomes after SARS-CoV-2 infections. High lipoprotein(a) [Lp(a)] concentrations are a strong risk factor for IHD and possibly for thromboembolic events. We therefore evaluated whether SARS-CoV-2 infections modify the risk of high Lp(a) concentrations for IHD or thromboembolic events during the first 8.5 months follow-up of the pandemic. METHOD: Cohort study using data from the UK Biobank during the SARS-CoV-2 pandemic. Baseline Lp(a) was compared between SARS-CoV-2 positive patients and the population controls. RESULTS: SARS-CoV-2 positive patients had Lp(a) concentrations similar to the population controls. The risk for IHD increased with higher Lp(a) concentrations in both, the population controls (n = 435,104) and SARS-CoV-2 positive patients (n = 6937). The causality of the findings was supported by a genetic risk score for Lp(a). A SARS-CoV-2 infection modified the association with a steeper increase in risk for infected patients (interaction p-value = 0.03). Although SARS-CoV-2 positive patients had a five-times higher frequency of thromboembolic events compared to the population controls (1.53% vs. 0.31%), the risk was not influenced by Lp(a). CONCLUSIONS: SARS-CoV-2 infections enforce the association between high Lp(a) and IHD but the risk for thromboembolic events is not influenced by Lp(a).

Cis-epistasis at the LPA locus and risk of cardiovascular diseases.

AIMS: Coronary artery disease (CAD) has a strong genetic predisposition. However, despite substantial discoveries made by genome-wide association studies (GWAS), a large proportion of heritability awaits identification. Non-additive genetic effects might be responsible for part of the unaccounted genetic variance. Here, we attempted a proof-of-concept study to identify non-additive genetic effects, namely epistatic interactions, associated with CAD. METHODS AND RESULTS: We tested for epistatic interactions in 10 CAD case-control studies and UK Biobank with focus on 8068 SNPs at 56 loci with known associations with CAD risk. We identified a SNP pair located in cis at the LPA locus, rs1800769 and rs9458001, to be jointly associated with risk for CAD [odds ratio (OR) = 1.37, P = 1.07 × 10-11], peripheral arterial disease (OR = 1.22, P = 2.32 × 10-4), aortic stenosis (OR = 1.47, P = 6.95 × 10-7), hepatic lipoprotein(a) (Lp(a)) transcript levels (beta = 0.39, P = 1.41 × 10-8), and Lp(a) serum levels (beta = 0.58, P = 8.7 × 10-32), while individual SNPs displayed no association. Further exploration of the LPA locus revealed a strong dependency of these associations on a rare variant, rs140570886, that was previously associated with Lp(a) levels. We confirmed increased CAD risk for heterozygous (relative OR = 1.46, P = 9.97 × 10-32) and individuals homozygous for the minor allele (relative OR = 1.77, P = 0.09) of rs140570886. Using forward model selection, we also show that epistatic interactions between rs140570886, rs9458001, and rs1800769 modulate the effects of the rs140570886 risk allele. CONCLUSIONS: These results demonstrate the feasibility of a large-scale knowledge-based epistasis scan and provide rare evidence of an epistatic interaction in a complex human disease. We were directed to a variant (rs140570886) influencing risk through additive genetic as well as epistatic effects. In summary, this study provides deeper insights into the genetic architecture of a locus important for cardiovascular diseases.

The size of apolipoprotein (a) is an independent determinant of the reduction in lipoprotein (a) induced by PCSK9 inhibitors.

AIMS: Lipoprotein (a) [Lp(a)] is a lipoprotein species causatively associated with atherosclerosis. Unlike statins, PCSK9 inhibitors (PCSK9i) reduce Lp(a), but this reduction is highly variable. Levels of Lp(a) are chiefly governed by the size of its signature protein, apolipoprotein (a) [apo(a)]. Whether this parameter determines some of the reduction in Lp(a) induced by PCSK9i remains unknown. We aimed to investigate if the Lp(a) lowering efficacy of PCSK9i is modulated by the size of apo(a), which is genetically determined by the variable number of KIV domains present on that protein. METHODS AND RESULTS: The levels of Lp(a) and the size of apo(a) were assessed in plasma samples from 268 patients before and after treatment with PCSK9i. Patients were recruited at the Outpatient Lipid Clinic of the Charité Hospital (Berlin) between 2015 and 2020. They were hypercholesterolaemic at very high cardiovascular disease risk with low-density lipoprotein (LDL)-cholesterol levels above therapeutic targets despite maximally tolerated lipid-lowering therapy. Patients received either Alirocumab (75 or 150 mg) or Evolocumab (140 mg) every 2 weeks. Apo(a), apoB100, and apoE concentrations as well as apoE major isoforms were determined by liquid chromatography high-resolution mass spectrometry. Apo(a) isoforms sizes were determined by western blot. PCSK9i sharply reduced LDL-cholesterol (-57%), apoB100 (-47%), and Lp(a) (-36%). There was a positive correlation between the size of apo(a) and the relative reduction in Lp(a) induced by PCSK9i (r = 0.363, P = 0.0001). The strength of this association remained unaltered after adjustment for baseline Lp(a) levels and all other potential confounding factors. In patients with two detectable apo(a) isoforms, there was also a positive correlation between the size of apo(a) and the reduction in Lp(a), separately for the smaller (r = 0.350, P = 0.0001) and larger (r = 0.324, P = 0.0003) isoforms. The relative contribution of the larger isoform to the total concentration of apo(a) was reduced from 29% to 15% (P < 0.0001). CONCLUSIONS: The size of apo(a) is an independent determinant of the response to PCSK9i. Each additional kringle domain is associated with a 3% additional reduction in Lp(a). This explains in part the variable efficacy of PCSK9i and allows to identify patients who will benefit most from these therapies in terms of Lp(a) lowering.

Lysis reagents, cell numbers, and calculation method influence high-throughput measurement of HDL-mediated cholesterol efflux capacity.

HDL-mediated cholesterol efflux capacity (CEC) may protect against cardiovascular disease. However, CEC assays are not standardized, hampering their application in large cohorts and comparison between studies. To improve standardization, we systematically investigated technical differences between existing protocols that influence assay performance that have not been previously addressed. CEC was measured in 96-well plates using J774A.1 macrophages labeled with BODIPY-cholesterol and incubated for 4 h with 2% apolipoprotein B-depleted human serum. The time zero method, which calculates CEC using control wells, and the per-well method, which calculates CEC based on the actual content of BODIPY-cholesterol in each well, were compared in 506 samples. We showed that the per-well method had a considerably lower sample rejection rate (4.74% vs. 13.44%) and intra-assay (4.48% vs. 5.28%) and interassay coefficients of variation (two controls: 7.85%, 9.86% vs. 13.58%, 15.29%) compared with the time zero method. Correction for plate-to-plate differences using four controls on each plate also improved assay performance of both methods. In addition, we observed that the lysis reagent used had a significant effect. Compared with cholic acid, lysis with sodium hydroxide results in higher (P = 0.0082) and Triton X-100 in lower (P = 0.0028) CEC values. Furthermore, large cell seeding errors (30% variation) greatly biased CEC for both referencing methods (P < 0.0001) as measured by a resazurin assay. In conclusion, lysis reagents, cell numbers, and assay setup greatly impact the quality and reliability of CEC quantification and should be considered when this method is newly established in a laboratory.

Frequent LPA KIV-2 Variants Lower Lipoprotein(a) Concentrations and Protect Against Coronary Artery Disease.

BACKGROUND: Lipoprotein(a) (Lp(a)) concentrations are a major independent risk factor for coronary artery disease (CAD) and are mainly determined by variation in LPA. Up to 70% of the LPA coding sequence is located in the hypervariable kringle IV type 2 (KIV-2) region. It is hardly accessible by conventional technologies, but may contain functional variants. OBJECTIVES: This study sought to investigate the new, very frequent splicing variant KIV-2 4733G>A on Lp(a) and CAD. METHODS: We genotyped 4733G>A in the GCKD (German Chronic Kidney Disease) study (n = 4,673) by allele-specific polymerase chain reaction, performed minigene assays, identified proxy single nucleotide polymorphisms and used them to characterize its effect on CAD by survival analysis in UK Biobank (n = 440,234). Frequencies in ethnic groups were assessed in the 1000 Genomes Project. RESULTS: The 4733G>A variant (38.2% carrier frequency) was found in most isoform sizes. It reduces allelic expression without abolishing protein production, lowers Lp(a) by 13.6 mg/dL (95% CI: 12.5-14.7; P < 0.0001) and is the strongest variance-explaining factor after the smaller isoform. Splicing of minigenes was modified. Compound heterozygosity (4.6% of the population) for 4733G>A and 4925G>A, another KIV-2 splicing mutation, reduces Lp(a) by 31.8 mg/dL and most importantly narrows the interquartile range by 9-fold (from 42.1 to 4.6 mg/dL) when compared to the wild type. In UK Biobank 4733G>A alone and compound heterozygosity with 4925G>A reduced HR for CAD by 9% (95% CI: 7%-11%) and 12% (95% CI: 7%-16%) (both P < 0.001). Frequencies in ethnicities differ notably. CONCLUSIONS: Functional variants in the previously inaccessible LPA KIV-2 region cooperate in determining Lp(a) variance and CAD risk. Even a moderate but lifelong genetic Lp(a) reduction translates to a noticeable CAD risk reduction.

When the genome bluffs: a tandem duplication event during generation of a novel Agmo knockout mouse model fools routine genotyping.

BACKGROUND: Genome editing in mice using either classical approaches like homologous recombination or CRISPR/Cas9 has been reported to harbor off target effects (insertion/deletion, frame shifts or gene segment duplications) that lead to mutations not only in close proximity to the target site but also outside. Only the genomes of few engineered mouse strains have been sequenced. Since the role of the ether-lipid cleaving enzyme alkylglycerol monooxygenase (AGMO) in physiology and pathophysiology remains enigmatic, we created a knockout mouse model for AGMO using EUCOMM stem cells but unforeseen genotyping issues that did not agree with Mendelian distribution and enzyme activity data prompted an in-depth genomic validation of the mouse model. RESULTS: We report a gene segment tandem duplication event that occurred during the generation of an Agmo knockout-first allele by homologous recombination. Only low homology was seen between the breakpoints. While a single copy of the recombinant 18 kb cassette was integrated correctly around exon 2 of the Agmo gene, whole genome nanopore sequencing revealed a 94 kb duplication in the Agmo locus that contains Agmo wild-type exons 1-3. The duplication fooled genotyping by routine PCR, but could be resolved using qPCR-based genotyping, targeted locus amplification sequencing and nanopore sequencing. Despite this event, this Agmo knockout mouse model lacks AGMO enzyme activity and can therefore be used to study its physiological role. CONCLUSIONS: A duplication event occurred at the exact locus of the homologous recombination and was not detected by conventional quality control filters such as FISH or long-range PCR over the recombination sites. Nanopore sequencing provides a cost convenient method to detect such underrated off-target effects, suggesting its use for additional quality assessment of gene editing in mice and also other model organisms.

Towards an SI-Traceable Reference Measurement System for Seven Serum Apolipoproteins Using Bottom-Up Quantitative Proteomics: Conceptual Approach Enabled by Cross-Disciplinary/Cross-Sector Collaboration.

Current dyslipidemia management in patients with atherosclerotic cardiovascular disease (ASCVD) is based on traditional serum lipids. Yet, there is some indication from basic research that serum apolipoproteins A-I, (a), B, C-I, C-II, C-III, and E may give better pathophysiological insight into the root causes of dyslipidemia. To facilitate the future adoption of clinical serum apolipoprotein (apo) profiling for precision medicine, strategies for accurate testing should be developed in advance. Recent discoveries in basic science and translational medicine set the stage for the IFCC Working Group on Apolipoproteins by Mass Spectrometry. Main drivers were the convergence of unmet clinical needs in cardiovascular disease (CVD) patients with enabling technology and metrology. First, the residual cardiovascular risk after accounting for established risk factors demonstrates that the current lipid panel is too limited to capture the full complexity of lipid metabolism in patients. Second, there is a need for accurate test results in highly polymorphic and atherogenic apolipoproteins such as apo(a). Third, sufficient robustness of mass spectrometry technology allows reproducible protein quantification at the molecular level. Fourth, several calibration hierarchies in the revised ISO 17511:2020 guideline facilitate metrological traceability of test results, the highest achievable standard being traceability to SI. This article outlines the conceptual approach aimed at achieving a novel, multiplexed Reference Measurement System (RMS) for seven apolipoproteins based on isotope dilution mass spectrometry and peptide-based calibration. This RMS should enable standardization of existing and emerging apolipoprotein assays to SI, within allowable limits of measurement uncertainty, through a sustainable network of Reference Laboratories.