The apo(a) gene (TTTTA)n promoter polymorphism and its association with variability in exons of the kringle IV types 8 to 10

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: β = -14.43 mg/dl, 95% CI: -15.84, -13.02, P = 3.33e-84; PNR11: β = -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: β = +0.44 mg/dl, 95% CI: -1.73, 2.60, P = 0.69; PNR11: β = -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 (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.

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) (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.

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.

Research advances in the influence of lipid metabolism on cognitive impairment

Cognitive impairment (CI) is a mental disorder related to cognition and understanding, which is mainly categorized into mild CI and senile dementia. This disease is associated with multiple factors, such as chronic brain injury, aging, chronic systemic disease, mental state, and psychological factors. However, the pathological mechanism of CI remains unclear; it is usually associated with such underlying diseases as diabetes and hyperlipidemia. It has been demonstrated that abundant lipid metabolism indexes in the human body are closely related to CI, including total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, apolipoprotein, and so forth. As a crucial risk factor for CI, hyperlipidemia is of great significance in the occurrence and development of CI. However, the specific correlation between dyslipidemia and CI is still not fully elucidated. Besides, the efficacy of lipid-lowering drugs in the prophylaxis and treatment of CI has not been clarified. In this study, relevant advances in the influence of lipid metabolism disorders in CI will be reviewed, in an attempt to explore the effect of mediating blood lipid levels on the prophylaxis and treatment of CI, thus providing a reference for its clinical management.

Comprehensive Analysis of Genomic Variation in the LPA Locus and Its Relationship to Plasma Lipoprotein(a) in South Asians, Chinese, and European Caucasians

Background— Functional copy number variation in the apolipoprotein(a) gene ( LPA ) underlies a variable number of protein kringle domains repeated in tandem in the lipoprotein(a) [Lp(a)] particle. Genomic analysis of LPA , including both single-nucleotide polymorphisms (SNPs) and kringle IV type 2 (KIV-2) copy number, has yet to be performed.

Methods and Results— First, we genotyped 49 SNPs within 100 kb of LPA in a multiethnic sample comprising South Asians (n=330), Chinese (n=304), and European Caucasians (n=272). Second, using quantitative polymerase chain reaction, we estimated the KIV-2 copy number in each sample. European Caucasians had the lowest KIV-2 copy number but displayed the strongest correlation between KIV-2 copy number and plasma Lp(a) concentration ( r s =−0.31, P =4.2�10 −7 ). SNP rs10455872, only prevalent in European Caucasians, was strongly associated with both plasma Lp(a) concentration ( P =4.2�10 −29 ) and KIV-2 copy number ( P =7.2�10 −5 ). LPA SNP rs6415084, within the same haplotype block as the KIV-2 variation, was significantly associated with both Lp(a) concentration and KIV-2 copy number in the same direction in all 3 ethnicities [Lp(a), P =5.3�10 −7 ; KIV-2, P =2.6�10 −4 ]. SNPs and KIV-2 copy number together explain a larger proportion of variation in plasma Lp(a) concentrations in European Caucasians (36%) than in Chinese (27%) or South Asians (21%).

Conclusions— LPA SNPs are in linkage disequilibrium with KIV-2 copy number, but KIV-2 copy number explains an increment in plasma Lp(a) variation over SNPs alone. Thus, both SNPs and KIV-2 copy number should be included in future genetic epidemiology studies of Lp(a).