Clinical Chemistry 63: (2017) Lipids, Lipoproteins, and Cardiovascular Risk Factors

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1 Clinical Chemistry 63: (2017) Lipids, Lipoproteins, and Cardiovascular Risk Factors Kringle IV Type 2, Not Low Lipoprotein(a), as a Cause of Diabetes: A Novel Genetic Approach Using SNPs Associated Selectively with Lipoprotein(a) Concentrations or with Kringle IV Type 2 Repeats Andra Tolbus, 1 Martin B. Mortensen, 2 Sune F. Nielsen, 1 Pia R. Kamstrup, 1 Stig E. Bojesen, 1,3,4 and Børge G. Nordestgaard 1,3,4* BACKGROUND: Low plasma lipoprotein(a) concentrations are associated with type 2 diabetes. Whether this is due to low lipoprotein(a) concentrations per se or to a large number of kringle IV type 2 (KIV-2) repeats remains unclear. We therefore aimed to identify genetic variants associated selectively with lipoprotein(a) concentrations or with the number of KIV-2 repeats, to investigate which of these traits confer risk of diabetes. METHODS: We genotyped 8411 individuals from the Copenhagen City Heart Study for 778 single-nucleotide polymorphisms (SNPs) in the proximity of the LPA gene, and examined the association of these SNPs with plasma concentrations of lipoprotein(a) and with KIV-2 number of repeats. SNPs that were selectively associated with lipoprotein(a) concentrations but not with KIV-2 number of repeats, or vice versa, were included in a Mendelian randomization study. RESULTS: We identified 3 SNPs (rs , rs , and rs641990) that were associated selectively with lipoprotein(a) concentrations and 3 SNPs (rs , rs , and rs ) that were associated selectively with KIV-2 number of repeats. For SNPs selectively associated with lipoprotein(a) concentrations, an allele score of 4 6 vs 0 2 had an odds ratio for type 2 diabetes of 1.03 (95% CI, ). In contrast, for SNPs selectively associated with KIV-2 number of repeats, an allele score of 4 6 vs 0 2 had an odds ratio for type 2 diabetes of 1.42 (95% CI, ). CONCLUSIONS: Using a novel genetic approach, our results indicate that it is a high number of KIV-2 repeats that are associated causally with increased risk of type 2 diabetes, and not low lipoprotein(a) concentrations per se. This is a reassuring finding for lipoprotein(a)- lowering therapies that do not increase the KIV-2 number of repeats American Association for Clinical Chemistry Increased lipoprotein(a) concentrations are causally associated with development of myocardial infarction and aortic valve stenosis (1 7). In contrast, low plasma lipoprotein(a) concentrations are observationally associated with increased risk of type 2 diabetes (8 11). Thus, there is a concern that treatment to lower plasma lipoprotein(a) to reduce cardiovascular disease could lead to an increased risk of type 2 diabetes. Indeed, with use of Mendelian randomization studies, a causal association between low lipoprotein(a) and type 2 diabetes has been confirmed (9). It is unclear, however, whether the increased risk of diabetes is due to low plasma lipoprotein(a) concentration per se or to large apo(a) isoform size. Lipoprotein(a) is a complex lipoprotein consisting of a single copy of a low-density lipoprotein particle covalently bound to apo(a) (4, 12, 13). Plasma concentrations of lipoprotein(a) are largely determined by genetic variation in the LPA gene coding for apo(a). Apo(a) contains 2 types of kringle domains: kringle IV and kringle V. While kringle IV type 1 and types 3 10 exist as single domains with a relatively constant size, kringle IV type 2 (KIV-2) exists in 3 to 40 copies per allele. The number of these KIV-2 repeats translates into apo(a) isoforms of increasing size and are inversely correlated with plasma lipoprotein(a) concentrations. Thus, large lipoprotein(a) isoforms are associated with low plasma concentrations 1 Department of Clinical Biochemistry and the Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark; 2 Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark; 3 The Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, Frederiksberg, Denmark; 4 Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. * Address correspondence to this author at: Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, Denmark. Fax ; boerge.nordestgaard@regionh.dk. Received May 28, 2017; accepted August 15, Previously published online at DOI: /clinchem American Association for Clinical Chemistry 1866

2 Kringle IV-2 as a Cause of Diabetes of lipoprotein(a), whereas small lipoprotein(a) isoforms are associated with high plasma concentrations. Almost half of the variations in lipoprotein(a) plasma concentrations is explained by the number of kringle IV type 2 repeats (and thus isoform size), while the rest is due to other known and unknown polymorphisms within the LPA gene region (13 16). To understand the pleiotropic effect of plasma lipoprotein(a) concentrations vs lipoprotein(a) isoform size for development of type 2 diabetes, genetic variants associated selectively with lipoprotein(a) concentrations and not with KIV-2 number of repeats, and vice versa, must be found. Thus, in the present study, we took advantage of the existent genotyped icogs (17 19) SNPs 5 with dense coverage in and around the LPA 6 gene in individuals enrolled in the Copenhagen City Heart Study. We identified novel SNPs selectively associated with lipoprotein(a) concentrations or with KIV-2 number of repeats, and applied them to examine a causal association with risk of type 2 diabetes, as attempted previously (9); however, in the previous study we used a genetic instrument that did not completely separate between lipoprotein(a) concentrations and KIV-2 number of repeats (9, 20), and thus was not definitive in answering this question. There are 2 novel aspects of the present study. First, we developed a new genetic approach to disentangle 2 different aspects of lipoprotein(a) biology and pathology: the role of lipoprotein(a) concentrations vs KIV-2 number of repeats. Second, we used this new approach to address the important clinical question of whether lowering of lipoprotein(a) concentrations is likely to cause diabetes. Methods COPENHAGEN CITY HEART STUDY The individuals included in our study belong to the examination of the Copenhagen City Heart Study, a prospective study of the general population, which comprises individuals sampled randomly from the white Danish adult general population living in the Copenhagen area. The individuals were subjected to a physical examination and were asked to fill in a questionnaire regarding lifestyle, health, and medical history. Blood samples were drawn for biochemical analyses. Of the individuals invited, participated, and we 5 Nonstandard abbreviations: SNPs, single-nucleotide polymorphisms; KIV-2, kringle IV type 2; COGS, Collaborative Oncological Gene-environment Study. 6 Human genes: LPA, lipoprotein (a); ALB, albumin; IGF2R, insulin like growth factor 2 receptor; SLC22A1, solute carrier family 22 member 1; SLC22A2, solute carrier family 22 member 2; SLC22A3, solute carrier family 22 member 3; LPAL2, lipoprotein (a) like 2, pseudogene; PLG, plasminogen. had lipoprotein(a) measurements, KIV-2 number of repeats, and icogs (18) genotypes on 8411 individuals. The study was approved by a Danish ethical committee ( /91) and was performed in accordance with the Declaration of Helsinki. All participants gave written informed consent. LIPOPROTEIN(A) CONCENTRATIONS The total plasma mass of lipoprotein(a) was measured turbidimetrically with use of a validated in-house method. The method, described thoroughly elsewhere (21), used a Technicon Axon autoanalyzer, rabbit antihuman lipoprotein(a) polyclonal antibodies, and a human serum lipoprotein(a) calibrator, and it was independent of lipoprotein(a) isoform size and thus of KIV-2 repeat genotype. The between series coefficients of variation at lipoprotein(a) concentrations of 9, 30, 42, 66, 100, and 127 mg/dl were 11%, 3%, 2%, 2%, 5%, and 4%, respectively. KRINGLE IV TYPE 2 REPEATS The total number of KIV-2 repeats was measured by use of a real-time polymerase chain reaction with the ABI Prism 7900 HT Sequence Detection System (Applied Biosystems), and the single-copy gene ALB to normalize for different DNA concentrations in the samples (3, 22). Thus, we were able to obtain the total number of KIV-2 repeats on both LPA alleles for each individual. GENOTYPING We used the icogs chip, a customized Illumina Infinium iselect array, designed by the Collaborative Oncological Gene-environment Study (COGS) (17 19). Each individual was genotyped for approximately SNPs. For the present study, we included 778 SNPs positioned 1.5 Mb in and around the LPA gene on chromosome 6 (160 Mb Mb). SNPs that were not in Hardy Weinberg equilibrium or showed evidence of genotyping errors were excluded from further analysis (n 6). The genotypes for the rs SNP (2) were also obtained by use of the TaqMan method (ABI PRISM 7900HT Sequence Detection System; Applied Biosystems). For the rs SNP genotype, the call rates for the icogs array and Taqman were 95% (MAF 1%) and 99.96%. The level of concordance between the 2 genotyping methods was 99.77%. Therefore, we used the Taqman genotypes in the analyses. TYPE 2 DIABETES Information on type 2 diabetes (International Classification of diseases 8th edition code 250, and 10th edition codes E11 and E13 14) was obtained from the national Danish Patient Registry and the national Danish Causes of Death Registry. To include diagnoses of type 2 diabetes made in general practice, we also assessed the ques- Clinical Chemistry 63:12 (2017) 1867

3 tionnaires for self-reported type 2 diabetes and/or use of diabetes medication. Additionally, individuals with nonfasting plasma glucose concentrations higher than 11 mmol/l (198 mg/dl) were also classified as having type 2 diabetes. Data Analysis and Statistics SNPS ASSOCIATED WITH LIPOPROTEIN(A) OR KIV-2 For statistical analyses, we used the R statistical platform (version 3.0.1) and PLINK (version 1.7.0). We first performed a SNP-quantitative trait association analysis using PLINK, which computes a least square regression analysis, returning the R 2 value, P value, and t-statistic for every association. The F value was calculated separately as F t 2, as a measure of the strength of the statistical instrument for instrumental variable analyses in Mendelian randomization studies. Other SNP parameters were also computed or extracted with use of R packages (SNPAssoc, Gefnetics, and NCBI2R packages): minor allele frequency, Hardy Weinberg equilibrium, and associated gene names. To identify SNPs associated selectively with either lipoprotein(a) concentrations or KIV-2 total number of repeats, we selected the top 100 SNPs with both the highest F values for association with lipoprotein(a) and F values 5 for the association with kringle IV type 2 repeats, and vice versa. For SNPs associated with both lipoprotein(a) concentrations and kringle IV type 2 repeats, we included those with highly significant F and P values for both associations. Linkage disequilibrium analyses for the SNPs related to each of the traits were performed with use of the LDHeatMap package in R, which uses the genotypes to compute the correlation parameters between the SNPs. SNPS ASSOCIATED WITH TYPE 2 DIABETES For studying the association of lipoprotein(a) concentrations or KIV-2 number of repeats with type 2 diabetes, we used logistic regression adjusted by age and sex. A scoring system was used to compute a joint allele score for the 2 groups of SNPs of interest [associated with lipoprotein(a) concentrations or with KIV-2 number of repeats]. For SNPs associated with lipoprotein(a) concentrations only, we labeled homozygous genotypes that lower lipoprotein(a) concentrations 2, homozygous genotypes that increase lipoprotein(a) concentrations 0, while heterozygous were labeled 1. Similarly, for the SNPs associated with number of KIV-2 repeats only, a score of 2 corresponded to homozygous genotypes increasing the number of KIV-2 repeats, 0 to homozygous genotypes lowering the number of KIV-2 repeats, while heterozygous genotypes were labeled 1. Considering that each group contains 3 SNPs, a cumulative score of 6 corresponds to the most extreme joint effect of the genotype in either lowering lipoprotein(a) concentrations or increasing the number of KIV-2 number of repeats. Thus, for each group, our cohort was split by allele score (7 groups with the allele scores 0 6). As the number of individuals was not equally distributed within the different allele groups, we combined individuals with the scores 0, 1, and 2 in a reference group to examine the risk of type 2 diabetes in individuals having allele scores of 3 or a combined group of 4, 5, and 6. These risk analyses were performed with use of logistic regression adjusted by sex and age. Results Baseline characteristics stratified by lipoprotein(a) concentrations and KIV-2 number of repeats for the 8411 individuals included in our study are shown in Table 1 in the Data Supplement that accompanies the online version of this article at vol63/issue12. The SNPs most strongly associated with lipoprotein(a) concentrations are listed in Tables 2 and 3 in the online Data Supplement, while the SNPs most strongly associated with KIV-2 number of repeats are listed in Tables 4 and 5 in the online Data Supplement: the SNPs specifically selected for the present study are highlighted with yellow [selectively associated with lipoprotein(a) concentrations] and green (selectively associated with KIV-2 number of repeats). More than 100 SNPs had F values above 100 for lipoprotein(a) concentrations, while 71 SNPs had F values above 100 for KIV-2 number of repeats. All 778 SNPs were examined extensively, but most SNPs were associated strongly both with lipoprotein(a) concentrations and with KIV-2 number of repeats. Thus, such SNPs cannot adequately address the current research question, unlike the 3 3 SNPs described below, either associated selectively with lipoprotein(a) concentrations or with KIV-2 number of repeats. To illustrate this point, we also describe the 3 SNPs associated most strongly with both lipoprotein(a) concentrations and with KIV-2 number of repeats. SNPS ASSOCIATED WITH EITHER LIPOPROTEIN(A) CONCENTRATIONS OR KIV-2 NUMBER OF REPEATS Fig. 1 shows Manhattan plots of SNPs in the IGF2R- SLC22A1-SLC22A2-SLC22A3-LPAL2-LPA-PLG gene cluster associated with plasma lipoprotein(a) concentrations (Fig. 1A) or with KIV-2 number of repeats (Fig. 1B). As illustrated, a number of SNPs were strongly associated with lipoprotein(a) concentrations and/or with KIV-2 repeats, yielding P values much lower than the typical genome-wide significance threshold of P Clinical Chemistry 63:12 (2017)

4 Kringle IV-2 as a Cause of Diabetes Fig. 1. Manhattan plots for SNP-lipoprotein(a) concentrations and SNP-kringle IV type 2 repeats associations in the LPA gene region, showing the distribution of icogs SNPs according to their association significance with each of the studied quantitative traits for lipoprotein(a) (A) and kringle IV type 2 (B) in the LPA gene region on chromosome 6 (approximately 160Mb 161.5Mb). The detailed structure of the LPA gene given at the bottom of the Fig. shows the multiple kringles (kringle IV (1 10) and kringle V) and singular protease domain. LPA, lipoprotein (a); IGF2R, insulin like growth factor 2 receptor; SLC22A1, solute carrier family 22 member 1; SLC22A2, solute carrier family 22 member 2; SLC22A3, solute carrier family 22 member 3; LPAL2, lipoprotein(a) like 2, pseudogene; PLG, plasminogen; KIV, kringle IV; KV, kringle V; P, protease domain. Clinical Chemistry 63:12 (2017) 1869

5 To assess the association of each SNP with the 2 quantitative traits, we plotted the significance parameters (F, P, and R 2 values) obtained from association analyses with both lipoprotein(a) and KIV-2 number of repeats (Fig. 2). There were SNPs with a high F value for one of the traits but low for the other one (Fig. 2A; Fig. 1A in the online Data Supplement). This was also observed for the P and R 2 values (Fig. 2, B and C; Fig. 1, B and C in the online Data Supplement). Then, for each quantitative trait we selected the top 100 SNPs with the highest F values. Additionally, for these selected SNPs we extracted the corresponding F values for the other quantitative trait. To identify SNPs that are only associated with one of the quantitative traits, while not associated with the other one, we then chose SNPs with F values 100 for lipoprotein(a) and F values 5 for KIV-2 number of repeats, and vice versa. SNPS ASSOCIATED WITH LIPOPROTEIN(A) CONCENTRATIONS ONLY We identified 3 SNPs (rs , rs , and rs641990) that were associated with lipoprotein(a) concentrations but not with kringle IV type 2 repeats (Fig. 3A C). The F ( 166), R 2 ( 2%), and P ( ) values for these associations with lipoprotein(a) concentrations were high compared to the association with number of KIV-2 repeats (F values 2 3, R 2 values 0.1%, P values ). The SNPs with the identifiers rs and rs are located within the LPA and SLC22A3 genes, respectively, whereas rs is located in an intergenic region downstream from LPA. SNPS ASSOCIATED WITH NUMBER OF KIV-2 REPEATS ONLY We identified 3 SNPs (rs , rs , and rs ) that were strongly associated with KIV-2 repeats but not with lipoprotein(a) plasma concentrations (Fig. 3, D F). The nonassociation was marked by smaller F (1 6), R 2 ( 0.1%), and P values ( ), than the association with number of KIV-2 repeats (F values 166, R 2 values 2% 5%, P values ). Additionally, the mean values for lipoprotein(a) plasma concentrations were relatively constant across genotypes, whereas the average number of KIV-2 repeats differed substantially. The SNP with the identifier rs (Fig. 3F) is situated in the LPA-like 2 pseudogene (LPAL2), whereas the other SNPs are located in intergenic or promoter regions. Three other SNPs fulfilling the condition of being associated with KIV-2 repeats only were identified (Fig. 2 in the online Data Supplement). These SNPs were in almost complete linkage disequilibrium with rs or rs (r ), and thus were not included in further analysis. The rs SNP is the only one located in the LPA gene region. Fig. 2. Association between lipoprotein(a) concentrations and kringle IV type 2 repeats using either F values, P values, or R 2 values. The figure displays the level of association for values of F, P, or R 2 for each SNP with both quantitative traits Clinical Chemistry 63:12 (2017)

6 Kringle IV-2 as a Cause of Diabetes Fig. 3. Significant SNP associations with lipoprotein(a) concentrations only (A C), with kringle IV type 2 repeats only (D F), and with both lipoprotein (a) concentrations and kringle IV type 2 repeats (G I). The figure shows mean values(95% CI) in lipoprotein(a) concentrations(green) and in number of kringle IV type 2 repeats(purple) for the SNPs associated with lipoprotein(a) concentrations only (A C), with kringle IV type 2 repeats only (D F), and with both lipoprotein(a) concentrations and kringle IV type 2 number of repeats (G I). Clinical Chemistry 63:12 (2017) 1871

7 Fig. 4. Risk of type 2 diabetes as a function of lipoprotein(a) concentrations in plasma and of number of kringle IV type 2 repeats on both alleles. Lipoprotein(a) plasma concentrations and the number of kringle IV type 2 repeats on both alleles are given as median (interquartile range). The logistic regression model was adjusted for age and sex. The events correspond to the number of type 2 diabetes cases. Total number of individuals, n = SNPS ASSOCIATED WITH BOTH LIPOPROTEIN(A) CONCENTRATIONS AND NUMBER OF KIV-2 REPEATS For comparison, we identified 3 SNPs (rs , rs , and rs ) that were most strongly associated with both lipoprotein(a) concentrations and KIV-2 number of repeats (Fig. 3, G I). The top hit rs was the SNP we used previously attempting to address the same question we address in the current study (9), clearly illustrating that our previous data were not definitive in answering this important question (20). LINKAGE DISEQUILIBRIUM BETWEEN SNPS Linkage disequilibrium analysis for SNPs associated with lipoprotein(a) concentrations only showed imperfect linkage equilibrium for the SNPs rs and rs with an r 2 value of 0.57 (Fig. 3, top panel, in the online Data Supplement). The correlation coefficients between rs and the other SNPs were closer to linkage equilibrium with r 2 values of 0.17 and The analyses for the SNPs associated with KIV-2 repeats only (Fig. 3, middle panel, in the online Data Supplement) revealed that the 3 SNPs in this group were almost in complete linkage equilibrium, having r 2 values close to 0 ( ). Linkage disequilibrium analyses for SNPs associated with both lipoprotein(a) concentrations and KIV-2 repeats are given in Fig. 3, bottom panel, in the online Data Supplement. RISK OF TYPE 2 DIABETES As expected, low lipoprotein(a) concentrations were observationally associated with increased risk of type 2 diabetes in our study population with an age- and sexadjusted odds ratio of 1.33 (95% CI, ) for the first quintile vs quintiles 2 5 (Fig. 4A). Likewise, a high number of KIV-2 repeats shared a similar trend, but did not reach statistical significance (Fig. 4B). For the SNPs selectively associated with lipoprotein(a) concentrations only, compared with an allele score of 6 corresponding to low lipoprotein(a) concentrations, lipoprotein(a) concentrations increased with lower allele scores (without changes in the number of KIV-2 repeats) (Fig. 5, left panels). Conversely, for SNPs associated with KIV-2 number of repeats only, compared with an allele score of 6 corresponding to a high number of KIV-2 repeats, the KIV-2 number of repeats decreased with lower allele scores (without changes in lipoprotein(a) concentrations; Fig. 5, right panels) Clinical Chemistry 63:12 (2017)

8 Kringle IV-2 as a Cause of Diabetes Fig. 5. Distribution of lipoprotein(a) concentrations (A) and the sum of kringle repeats (B) per allele score for the SNPs associated with lipoprotein(a) concentrations only (left panels) and kringle IV type 2 repeats only (right panels). The SNPs selectively affecting lipoprotein(a) concentrations did not associate with the risk of type 2 diabetes (Fig. 6A) with an odds ratio of 1.03 (95% CI, ) for an allele score of 4 6 vs 0 2. In contrast, SNPs selectively associated with the KIV-2 number of repeats increased the risk of type 2 diabetes (Fig. 6B) with an odds ratio of 1.42 (95% CI, ) for an allele score of 4 6 vs 0 2; these results were similar after adjusting for lipoprotein(a) concentrations (data not shown). Discussion Increased lipoprotein(a) concentration is a wellestablished causal risk factor for development of cardiovascular disease (1 7). However, it came as a surprise when low concentrations of lipoprotein(a) were shown to be associated with risk of type 2 diabetes (8). This association has been confirmed in several independent studies (9 11). Thus, an emerging concern is whether treatment of high lipoprotein(a) concentrations given to reduce the risk of cardiovascular disease could lead to a counterproductive development of type 2 diabetes (16). To exclude the possibility of reverse causation or confounding by these observational studies, we recently carried out a Mendelian randomization study showing that high number of KIV-2 repeats did indeed associate causally with increased diabetes risk (9). However, whether this is mediated by large isoform size or by low plasma concentrations remains unclear due to the pleiotropic effects of the genetic variants [associated with both large lipoprotein(a) isoform size and low plasma concentrations] used in these analyses. Although we used the rs SNP [mainly affecting lipoprotein(a) concentrations in plasma] to demonstrate that it is likely not low plasma concentrations of lipoprotein(a) per se that cause type 2 diabetes, we did not provide direct evidence that the increased risk of diabetes is conferred by large Clinical Chemistry 63:12 (2017) 1873

9 Fig. 6. Risk of type 2 diabetes as a function of combined allele scores for the SNPs associated with (A) lipoprotein(a) concentrations only and (B) kringle IV type 2 repeats only. Sex- and age-adjusted logistic regression analysis for combined allele scores and risk of diabetes. lipoprotein(a) isoform size. Indeed, the present study shows that carrier or noncarrier status of the rs SNP affects both lipoprotein(a) concentrations and KIV-2 number of repeats with F values 1500 for both traits. Further, others have pointed out that the carrier or noncarrier status of the rs SNP may not be an optimal instrument to investigate causality of low lipoprotein(a) concentrations and risk of type 2 diabetes in the general population (20, 23). The novel finding of the present study is that we clearly demonstrate that SNPs only associated with KIV-2 number of repeats are causally associated with high risk of type 2 diabetes, while SNPs only associated with lipoprotein(a) concentrations are not. In the present study, we developed a novel genetic approach to better understand the effects of plasma lipoprotein(a) concentrations vs lipoprotein(a) isoforms size (determined by KIV-2 number of repeats) by identifying SNPs associated selectively with lipoprotein(a) concentrations but not with KIV-2 number of repeats, and vice versa. To do so, we tested 778 SNPs located in the proximity of the LPA gene region on chromosome 6 for significant and unique associations with 1 of the 2 quantitative traits of interest. These SNPs have been genotyped as part of the icogs (18) project including roughly 9000 individuals from the Copenhagen City Heart Study. Using this extensive data set, we were able to identify triads of SNPs selectively associated with lipoprotein(a) concentrations or with KIV-2 number of repeats, without significantly affecting the other trait. Observationally, our findings are in line with results from the previous studies in which low plasma concentration of lipoprotein(a) is associated with an increased risk of type 2 diabetes (8, 9, 11). Although the sum of 1874 Clinical Chemistry 63:12 (2017)

10 Kringle IV-2 as a Cause of Diabetes KIV-2 repeats did not reach a statistically significant association with type 2 diabetes in the current analyses despite a clear trend, we have previously demonstrated such an association (9). Considering that the current study population comprises only a fraction of the population analyzed previously by us (9), we argue that the slight difference in results between the 2 studies is merely due to a statistical power issue in the present study. Further, the apparent weaker observational association with diabetes for KIV-2 number of repeats compared with that for lipoprotein(a) concentrations may be explained by methodology. As we measured KIV-2 number of repeats with use of real-time PCR, the obtained value is the mean of the number of repeats at the 2 different LPA alleles. Therefore, as it appears to be large KIV-2 number of repeats that causes diabetes and not average particle size, our measurement of average KIV-2 number of repeats will tend to bias our results toward the null hypothesis of no association. Interestingly, from a genetic point of view, our analyses using calculated cumulative allele score for each triad of SNPs revealed that the genotypes that lower lipoprotein(a) concentrations are not associated with an increased risk of diabetes when the number of KIV-2 repeats remains constant [for SNPs associated with lipoprotein(a) concentrations only], whereas the genotypes that increases the number of KIV-2 repeats are associated with an increased risk of diabetes when plasma concentrations lipoprotein(a) are kept constant (for the SNPs solely associated with KIV-2 number of repeats). Taken together, these results build upon our previous findings indicating that it is indeed large isoform size of lipoprotein(a) that is causally associated with risk of type 2 diabetes, and not low concentrations of plasma lipoprotein(a) as suggested by observational studies. Although we cannot explain how large isoform size of lipoprotein(a) causes type 2 diabetes, our results are nevertheless reassuring for the future use of lipoprotein(a)-lowering drugs that do not increase KIV-2 number of repeats as a means to lower cardiovascular disease risk (23). That being said, it is not known whether PCSK9-inhibitors or other lipoprotein(a) lowering therapies increase the number of KIV-2 repeats; however, we believe that this is unlikely because the KIV-2 number of repeats is determined by genetics, that is, by the 2 LPA alleles. Thus, even if lipoprotein(a)-lowering therapies selectively reduce the concentration of small particles with low number of KIV-2 repeats, there is no apparent reason why this should lead to a higher concentration of large particles with a high number of KIV-2 repeats. However, whether the ratio of large to small particles changes in response to lipoprotein(a)-lowering therapies is unknown, as is any potential clinical consequence of such a change. Finally, the impact of lipoprotein(a) isoform size on type 2 diabetes clearly warrants further research to clarify the underlying pathophysiological mechanism as it may point to new targets for prevention and treatment of diabetes. Limitations The potential limitations of Mendelian randomizations studies have been discussed previously (24 26), including linkage disequilibrium with genetic variants associated with the disease of interest. Although we cannot completely exclude pleiotropic effects or linkage disequilibrium of one or more of the SNPs used in our allele scores, the totality of our data including a stepwise association of the number of KIV-2 repeats with risk of type 2 diabetes makes it very unlikely that our results are caused by such limitations. Further, the LPA KIV-2 polymorphisms used in our previous Mendelian randomization study to demonstrate a causal association of lipoprotein(a) with diabetes risk is not in linkage disequilibrium with any genes so far implicated in risk of type 2 diabetes (9, 27 29). Conclusions With use of a novel genetic approach, our results indicate that it is a high number of KIV-2 repeats that are associated causally with increased risk of type 2 diabetes in the general population, and not low lipoprotein(a) concentrations. For prevention of cardiovascular disease, these results provide reassurance for the use of lipoprotein(a)- lowering therapies that do not increase KIV-2 number of repeats. Future studies are needed to understand the pathophysiological mechanism behind the causal association between lipoprotein(a) isoform size and type 2 diabetes, as this may point to new targets for treatment of diabetes. Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article. Authors Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest: Employment or Leadership: None declared. Consultant or Advisory Role: P.R. Kamstrup, Sanofi; B.G. Nordestgaard, AstraZeneca, Isis Pharmaceuticals, Amgen, Dezima, Sanofi and Regeneron. Stock Ownership: None declared. Honoraria: P.R. Kamstrup, Fresenius Medical Care; B.G. Nordestgaard, AstraZeneca, Isis Pharmaceuticals, Amgen, Dezima, Sanofi and Regeneron. Clinical Chemistry 63:12 (2017) 1875

11 Research Funding: Funding for the icogs infrastructure came from: the European Community s Seventh Framework Programme under grant agreement n (HEALTH-F ) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/ A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/ A10692), the National Institutes of Health (CA128978) and Post- Cancer GWAS initiative (1U19 CA148537, 1U19 CA and 1U19 CA the GAME-ON initiative), the Department of Defence (W81XWH ), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The Copenhagen City Heart Study is funded by the Danish Heart Foundation. References Expert Testimony: None declared. Patents: None declared. Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or final approval of manuscript. Acknowledgment: This COGS study would not have been possible without the contributions of the staff from the following institutions: BCAC, OCAC, PRACTICAL, CIMBA, Centre for Genetic Epidemiology Laboratory, CNIO genotyping unit, McGill University and Génome Québec Innovation Centre, Copenhagen DNA laboratory, and Mayo Clinic Genotyping Core Facility. 1. Emerging Risk Factors Collaboration, Erqou S, Kaptoge S, Perry PL, Di Angelantonio E, Thompson A, et al. Lipoprotein (a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality. JAMA 2009; 302: Clarke R, Peden JF, Hopewell JC, Kyriakou T, Goel A, Heath SC, et al. Genetic variants associated with Lp(a) lipoprotein level and coronary disease. N Engl J Med 2009;361: Kamstrup PR, Tybjaerg-Hansen A, Steffensen R, Nordestgaard BG. Genetically elevated lipoprotein(a) and increased risk of myocardial infarction. JAMA 2009; 301: Nordestgaard BG, Chapman MJ, Ray K, Borén J, Andreotti F, Watts GF, et al. Lipoprotein(a) as a cardiovascular risk factor: current status. Eur Heart J 2010;31: Thanassoulis G, Campbell CY, Owens DS, Smith JG, Smith AV, Peloso GM, et al. Genetic associations with valvular calcification and aortic stenosis. N Engl J Med 2013;368: Kamstrup PR, Tybjaerg-Hansen A, Nordestgaard BG. Elevated lipoprotein(a) and risk of aortic valve stenosis in the general population. J Am Coll Cardiol 2014;63: Nordestgaard BG, Langsted A. Lipoprotein (a) as a cause of cardiovascular disease: insights from epidemiology, genetics, and biology. J Lipid Res 2016;57: Mora S, Kamstrup PR, Rifai N, Nordestgaard BG, Buring JE, Ridker PM. Lipoprotein(a) and risk of type 2 diabetes. Clin Chem 2010;56: Kamstrup PR, Nordestgaard BG. Lipoprotein (a) concentrations, isoform size, and risk of type 2 diabetes: a Mendelian randomisation study. Lancet Diabetes Endocrinol 2013;1: Ye Z, Haycock PC, Gurdasani D, Pomilla C, Boekholdt SM, Tsimikas S, et al. The association between circulating lipoprotein(a) and type 2 diabetes: is it causal? Diabetes 2014;63: Ding L, Song A, Dai M, Xu M, Sun W, Xu B, et al. Serum lipoprotein (a) concentrations are inversely associated with T2D, prediabetes, and insulin resistance in a middle-aged and elderly Chinese population. J Lipid Res 2015;56: BergK. Anewserumtypesysteminman-TheLPsystem. Acta Pathol Microbiol Scand 1963;59: Schmidt K, Noureen A, Kronenberg F, Utermann G. Structure, function, and genetics of lipoprotein (a). J Lipid Res 2016;57: Berg K, Mohr J. Genetics of the LP system. Acta Genet Stat Med 1963;13: Ober C, Nord AS, Thompson EE, Pan L, Tan Z, Cusanovich D, et al. Genome-wide association study of plasma lipoprotein (a) levels identifies multiple genes on chromosome 6q. J Lipid Res 2009;50: Kronenberg F, Utermann G. Lipoprotein(a): resurrected by genetics. J Intern Med 2013;273: Michailidou K, Hall P, González-Neira A, Ghoussaini M, Dennis J, Milne RL, et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet. 2013;45:353 61, 316e Bojesen SE, Pooley KA, Johnatty SE, Beesley J, Michailidou K, Tyrer JP, et al. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nat Genet 2013;45: , 384e Eeles RA, Olama AAA, Benlloch S, Saunders EJ, Leongamornlert DA, Tymrakiewicz M, et al. Identification of 23 new prostate cancer susceptibility loci using the icogs custom genotyping array. Nat Genet 2013;45:385 91,391e Lamina C, Kronenberg F. The mysterious lipoprotein(a) is still good for a surprise. Lancet Diabetes Endocrinol 2013;1: Kamstrup PR, Benn M, Tybjaerg-Hansen A, Nordestgaard BG. Extreme lipoprotein (a) levels and risk of myocardial infarction in the general population: the Copenhagen City Heart Study. Circulation 2008;117: Kamstrup PR, Tybjaerg-Hansen A, Nordestgaard BG. Extreme lipoprotein(a) levels and improved cardiovascular risk prediction. J Am Coll Cardiol 2013;61: Kronenberg F. Human genetics and the causal role of lipoprotein (a) for various diseases. Cardiovasc Drugs Ther 2016;30: Burgess S, Thompson SG. Use of allele scores as instrumental variables for Mendelian randomization. Int J Epidemiol 2013;42: Kamstrup PR, Nordestgaard BG. Elevated lipoprotein (a) levels, LPA risk genotypes, and increased risk of heart failure in the general population. JACC Heart Fail 2016;4: Burgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat Med 2016;35: Stolerman ES, Florez JC. Genomics of type 2 diabetes mellitus: implications for the clinician. Nat Rev Endocrinol 2009;5: Ahlqvist E, Ahluwalia TS, Groop L. Genetics of type 2 diabetes. Clin Chem 2011;57: Sanghera DK, Blackett PR. Type 2 diabetes genetics: beyond GWAS. J Diabetes Metab 2012; Clinical Chemistry 63:12 (2017)