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Department of Vascular Medicine, Amsterdam UMC, Location AMC, Meibergdreef 9, 1105 AZ, Amsterdam, the NetherlandsDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
Department of Vascular Medicine, Amsterdam UMC, Location AMC, Meibergdreef 9, 1105 AZ, Amsterdam, the NetherlandsDepartment of Internal Medicine, OLVG Oost, Amsterdam, the Netherlands
Corresponding author. Amsterdam University Medical Centers, Department of Vascular Medicine, room D3-330, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands.
High Lp(a) partly explains clinical FH in patients in whom no FH-variant is identified.
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Up to 9% of patients lose a clinical FH diagnosis using Lp(a)-corrected LDL-C.
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Using Lp(a) reclassifies up to 1 in 5 patients towards a higher ASCVD risk category.
Abstract
Background and aims
Lipoprotein(a) (Lp(a)) is an LDL-like particle whose plasma levels are largely genetically determined. The impact of measuring Lp(a) in patients with clinical familial hypercholesterolemia (FH) referred for genetic testing is largely unknown. We set out to evaluate the contribution of (genetically estimated) Lp(a) in a large nation-wide referral population of clinical FH.
Methods
In 1504 patients referred for FH genotyping, we used an LPA genetic instrument (rs10455872 and rs3798220) as a proxy for plasma Lp(a) levels. The genetic Lp(a) proxy was used to correct LDL-cholesterol and reclassify patients with clinical FH based on Dutch Lipid Criteria Network (DLCN) scoring. Finally, we used estimated Lp(a) levels to reclassify ASCVD risk using the SCORE and SMART risk scores.
Results
LPA SNPs were more prevalent among mutation-negative compared with mutation-positive patients (296/1280 (23.1%) vs 35/224 (15.6%), p = 0.016). Among patients with genetically defined high Lp(a) levels, 9% were reclassified to the DLCN category ‘unlikely FH’ using Lp(a)-corrected LDL-cholesterol (LDL-Ccor) and all but one of these patients indeed carried no FH variant. Furthermore, elevated Lp(a) reclassified predicted ASCVD risk into a higher category in up to 18% of patients.
Conclusions
In patients referred for FH molecular testing, we show that taking into account (genetically estimated) Lp(a) levels not only results in reclassification of probability of genetic FH, but also has an impact on individual cardiovascular risk evaluation. However, to avoid missing the diagnosis of an FH variant, clear thresholds for the use of Lp(a)-cholesterol adjusted LDL-cholesterol levels in patients referred for genetic testing of FH must be established.
Familial hypercholesterolemia (FH) is a genetic disorder characterized by high plasma LDL-cholesterol levels from birth onwards, leading to a high risk for atherosclerotic cardiovascular disease (ASCVD) if left untreated [
Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus Statement of the European Atherosclerosis Society.
]. Patients with genetically confirmed FH are at increased risk of ASCVD compared with individuals with equal LDL-cholesterol levels not carrying an FH variant; a finding that reflects the effect of lifelong exposure to elevated LDL-cholesterol levels [
Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus Statement of the European Atherosclerosis Society.
]. However, the prevalence of genetic FH among patients referred with clinically suspected FH varies greatly between studies, which is probably related to differences in the clinical criteria used to estimate the probability of finding an FH causing variant [
Molecular genetic testing for autosomal dominant hypercholesterolemia in 29,449 Norwegian index patients and 14,230 relatives during the years 1993–2020.
]. Preselecting patients with hypercholesterolemia based on clinical scoring criteria, which includes LDL cholesterol as a major criterion, improves the chance of finding a pathogenic FH variant. In the Netherlands, only 15% of patients with a clinical suspicion of FH and an untreated LDL-cholesterol level exceeding 5 mmol/L (corresponding to Dutch Lipid Clinic Network (DLCN) score of ‘possible FH’ or higher), were found to carry a (likely) pathogenic FH variant [
]. This number increased to 54% in patients with LDL-cholesterol levels ≥8 mmol/L.
It is increasingly clear that cholesterol reported in the LDL fraction by routine clinical laboratories includes cholesterol that is actually carried by another lipoprotein class: lipoprotein(a) (Lp(a)) [
]. Lp(a) levels are largely genetically determined, therefore remain constant throughout life and are only marginally influenced by diet, lifestyle and currently widely prescribed lipid lowering medication [
]. Circulating concentrations of Lp(a) correlate to the number of kringle IV type 2 repeats and other variations in the LPA gene, of which the common LPA single-nucleotide polymorphisms (SNPs) rs10455872 (intronic, non-coding) and rs3798220 (missense variant Ile399Met in the apolipoprotein(a) protease-like domain) are most strongly associated with Lp(a) levels [
]. It has been shown that genetic instruments serve as a reliable proxy for Lp(a) levels and are associated with Lp(a) attributable increased ASCVD risk [
Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study.
Association of LPA variants with risk of coronary disease and the implications for lipoprotein(a)-lowering therapies: a mendelian randomization analysis.
Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study.
]. Since routine laboratory assays do not discriminate between cholesterol carried in Lp(a) or LDL particles, the reported LDL-cholesterol is inflated by the cholesterol contained in the Lp(a) fraction [
Relationship between “LDL-C” estimated true LDL-C, apolipoprotein B-100, and PCSK9 levels following lipoprotein(a) lowering with an antisense oligonucleotide.
Familial combined hyperlipidemia and hyperlipoprotein(a) as phenotypic mimics of familial hypercholesterolemia: frequencies, associations and predictions.
]. In brief, patients with a clinical suspicion of FH who were referred for genetic analysis of dyslipidemia at Amsterdam University Medical Centers between 2016 and 2018 were eligible for inclusion. Patients with reported triglyceride levels >4.5 mmol/L, LDL-cholesterol levels <5 mmol/L and/or lipid levels obtained while on lipid lowering therapy were excluded from the study. Patients provided written consent for re-use of data for research purposes.
In this overall Dutch FH cohort, Lp(a) levels could not be measured since plasma is unavailable and only DNA is stored. We therefore invited a subgroup of patients from the overall Dutch FH cohort for a detailed study visit. Inclusion criteria for this subgroup were a DLCN score of ‘probable FH’ or higher upon referral and absence of a pathogenic FH variant after NGS (i.e. mutation-negative subgroup) and researchers were blinded to LPA genotyping results before contacting patients. Patients in the mutation-negative subgroup provided written informed consent and the study was approved by the institution's ethics committee on research on humans (NL62407.018.17).
2.2 DNA isolation and FH genotyping
DNA isolation and FH genotyping procedures were performed in all patients and have been described previously [
]. In brief, clinicians shipped a blood sample from patients in whom, based on clinical phenotypes, they suspected a genetic form of dyslipidemia. At the nationwide central facility at Amsterdam UMC, DNA was isolated and subsequently a total of 29 lipid related genes including LDLR, APOB and PCSK9, were analyzed using an in-house next-generation sequencing (NGS) capture array (SeqCap easy choice; Roche NimbleGen Inc., Pleasanton, USA). Two trained molecular geneticists assessed all variants in the exons and at least 20 base pairs in the adjacent introns of these sequenced genes for their pathogenicity according to standard guidelines for variant classification of the American College of Medical Genetics and Genomics [
Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of medical genetics and Genomics and the association for molecular pathology.
]. Patients carrying a class 4 (likely pathogenic) or class 5 (pathogenic) variant in LDLR, APOB or PCSK9 were diagnosed with heterozygous FH. DNA was stored at 5 °C for future re-analysis and/or research purposes.
2.3 LPA genotyping and estimation of Lp(a) levels
Genotyping of the rs10455872 and rs3798220 loci was performed in all patients using TaqMan SNP Genotyping Assays (ThermoFisher Scientific, assays C__30,016,089_10 and C__25,930,271_10, respectively). Reactions were performed in 10 μL final volume with TaqMan Genotyping Master Mix according to the manufacturer's instructions (ThermoFisher Scientific, catalog #4351379). Assays were performed on a CFX384 Touch Real Time PCR detection System and analyzed using CFX Manager v3.1 software.
Next, we estimated the Lp(a) levels of LPA SNP carriers in the Dutch FH cohort. For this, we used data from >400.000 participants of the UK Biobank described by Kronenberg and colleagues, which linked these SNPs to Lp(a) levels (measured in nmol/L) [
]. In this study, patients with one risk allele were shown to have a median Lp(a) level of 146.3 nmol/L (63.6 mg/dL), and those with two risk alleles were shown to have a median Lp(a) level of 261.9 nmol/L (113.9 mg/dL, conversion from nmol/L to mg/dL was performed by dividing by 2.3) [
Lipid panels from the overall Dutch FH cohort were physician-reported and we performed laboratory tests in plasma collected from patients in the mutation-negative subgroup. Patients from the mutation-negative subgroup were visited by one of the researchers who collected blood, a detailed medical history, family history and anthropomorphic measurements. To rule out any potential influence of lipid lowering therapy on Lp(a) levels, blood was taken off-therapy following a washout period of at least 4 weeks. Following an overnight fast, blood was drawn in vacutainers, immediately put on ice, centrifuged for 15 min at 3000 g and plasma was stored at −80C awaiting laboratory testing.
In the mutation-negative subgroup, Lp(a) was measured in nmol/L by an isoform insensitive, second-generation assay (Roche Diagnostics, Mannheim, Germany) which is traceable to an internationally accepted calibrator (World Health Organization-approved IFCC reference standard Apo(a), SRM 2 B). Total cholesterol, HDL-cholesterol and triglyceride levels were determined by our central laboratory facility and LDL-cholesterol was calculated by the Friedewald formula. Lp(a) corrected levels of LDL-cholesterol (LDL-Ccor) were calculated by subtracting 17.3% of Lp(a) mass from LDL-cholesterol. This number is based on the study by Yeang et al. and is the median percentage of Lp(a)-cholesterol quantified directly [
]. It is of note that this correction provides a more conservative estimate compared to the historically used Dahlen formula, which assumes 30% of Lp(a) mass is cholesterol. We performed sensitivity analyses with the Dahlen formula to facilitate direct comparison with previous studies that have used this equation [
]. Patients with genetically confirmed FH were excluded from these analyses because the risk tools are not validated for this patient population. First, we used the established algorithms SCORE [
Development and validation of a prediction rule for recurrent vascular events based on a cohort study of patients with arterial disease: the SMART risk score.
] for patients with prior CVD, to calculate 10-year predicted risk of CVD mortality and recurrent vascular events, respectively. Missing values were imputed with the population average provided by the online SMART score calculator (u-prevent.com).
Next, we multiplied the SCORE and SMART score with ORs for genetically predicted Lp(a) increase above the population average from two observational cohorts in both primary and secondary prevention. For primary prevention, we added genetically predicted Lp(a) levels to the SCORE algorithm using the following formula:
This formula was based on the observation in the UK Biobank that every 50 nmol/L increase above the median results in a hazard ratio of 1.04 for recurrent ASCVD events [
]. Predicted risk of recurrent ASCVD events was classified into five categories: <10% was classified as low, 10–20% as moderate, 20–30% as high, 30–40% as very high, and >40% as extremely high risk [
Development and validation of a prediction rule for recurrent vascular events based on a cohort study of patients with arterial disease: the SMART risk score.
Statistical analyses were performed using R, version 4.0.3 (R Foundation, Vienna, Austria). Categorical variables are presented as n (%) and continuous variables are presented as median (IQR) or mean (±SD), as appropriate. Comparisons were made using the unpaired T-test, Mann–Whitney U test, and chi-squared test, as appropriate. A two-sided p-value <0.05 was considered statistically significant.
3. Results
Of the 2320 index patients referred for genetic analysis of dyslipidemia between May 2016 and July 2018, we excluded patients in whom no treatment-naïve LDL-cholesterol >5 mmol/L (n = 792) was reported and patients in whom LPA genotype was unavailable (n = 24). The remaining 1504 patients were used in the current analyses (Supplemental Fig. 1). Baseline characteristics of this population, overall and stratified for FH variant carrier status, are shown in Table 1. Overall, 897 (69.6%) patients were female, mean age was 52.8 ± 13.1 years, mean body mass index (BMI) was 26.7 ± 4.1 kg/m2, mean LDL-cholesterol level was 6.3 ± 1.0 mmol/L, and 327 (22.0%) patients had a history of cardiovascular disease. Smoking and diabetes were present in 294 (20.2%) and 69 (4.8%) patients, respectively. Patients carrying a pathogenic FH variant (FH/M+) had higher LDL-cholesterol (mean 7.10 ± 1.40 vs 6.16 ± 0.86 mmol/L, p < 0.001) and lower triglyceride levels (median 1.5 [1.0–2.1] vs 1.9 [1.4–2.6] mmol/L, p < 0.001) compared with patients without (FH/M-). FH/M- patients more frequently carried an Lp(a)-raising SNP (either rs10455872 and/or rs3798220) compared with FH/M+ patients (296/1280 (23.1%) vs 35/224 (15.6%), p = 0.016, Fig. 1).
Table 1Baseline characteristics of the Dutch FH cohort, overall and according to FH mutation status.
Overall
FH/M-
FH/M+
p-value
N = 1504
N = 1280
N = 224
Female sex, n (%)
897 (69.6)
770 (60.2)
127 (56.7)
0.368
Age (years), mean ± SD
52.8 (13.1)
54.5 (11.7)
43.5 (16.5)
<0.001
BMI (kg/m2), mean ± SD
26.7 (4.1)
26.7 (4.0)
26.1 (4.6)
0.071
Diabetes mellitus, n (%)
69 (4.8)
64 (5.2)
5 (2.5)
0.001
Current smoker, n (%)
294 (20.2)
257 (20.7)
37 (17.2)
0.345
Total cholesterol (mmol/L), mean ± SD
8.5 (1.1)
8.43 (1.00)
9.17 (1.57)
<0.001
LDL-cholesterol (mmol/L), mean ± SD
6.3 (1.0)
6.16 (0.86)
7.10 (1.40)
<0.001
HDL-cholesterol (mmol/L), mean ± SD
1.4 (0.4)
1.42 (0.41)
1.36 (0.47)
0.067
Triglycerides, median [IQR]
1.8 [1.4–2.5]
1.9 [1.4–2.6]
1.5 [1.0–2.1]
<0.001
Parent history of CVD, n (%)
707 (57.6)
608 (58.6)
99 (52.1)
0.014
Patient history of any CVD, n (%)
327 (22.0)
292 (23.1)
35 (15.9)
0.046
Myocardial infarction, n (%)
129 (8.7)
112 (8.9)
17 (7.7)
0.445
CABG, n (%)
52 (3.5)
43 (3.4)
9 (4.1)
0.014
PCI, n (%)
122 (8.2)
109 (8.6)
13 (5.9)
0.002
Angina pectoris, n (%)
139 (9.4)
122 (9.6)
17 (7.7)
0.640
Stroke, n (%)
65 (4.4)
62 (4.9)
3 (1.4)
0.005
Peripheral artery disease, n (%)
57 (3.8)
55 (4.3)
2 (0.9)
0.001
LPA SNP carrier (rs10455872 and/or rs3798220), n (%)
331 (22.0)
296 (23.1)
35 (15.6)
0.016
DLCN category (excl. genetics)
Possible FH
1061 (70.5)
957 (74.8)
104 (46.4)
<0.001
Probable FH
357 (23.7)
272 (21.2)
85 (37.9)
Definite FH
86 (5.7)
51 (4.0)
35 (15.6)
Smoking status was known for 1458 patients, diabetes mellitus status was known for 1435 patients, patient CVD history was known for 1485 patients, parental CVD history was known for 1227 patients. p-value represents comparison between FH/M- and FH/M+ groups.
BMI, body mass index; CABG, coronary artery bypass grafting; CVD, cardiovascular disease, PCI, percutaneous coronary intervention; SNP, single nucleotide polymorphism; DLCN, Dutch Lipid Clinic Network; FH, familial hypercholesterolemia.
Since Lp(a) levels were unavailable in the overall Dutch FH cohort, we next sought to ascertain the prevalence and correlation of the LPA SNPs with Lp(a) levels in a subgroup of FH/M- patients from the overall cohort. Patient characteristics were similar to the overall Dutch FH cohort (Supplementary Table 2). Indeed, we found that measured Lp(a) levels were higher in LPA SNP carriers. Compared with the remainder of the mutation-negative subgroup, median [IQR] Lp(a) levels were higher in those carrying any number of LPA SNPs (238 [161–323] vs 19 [10–42] nmol/L, p < 0.001, Supplementary Fig. 2A). The highest Lp(a) levels were observed in patients who were found to carry two LPA SNPs (two bi-allelic carriers of rs10455872 and two patients with both rs10455872 and rs3798220 with median Lp(a) levels of 489 [423, 513] nmol/L, Supplementary Fig. 2A). No bi-allelic carriers of rs3798220 were found.
Having verified the correlation with LPA SNPs and measured plasma Lp(a) levels in the mutation-negative subgroup, we next used genetically estimated Lp(a) levels to derive Lp(a)-cholesterol corrected LDL-cholesterol levels (LDL-Ccor) in the entire Dutch FH cohort. Based on these LDL-Ccor levels we subsequently modelled the reclassification in clinical FH scoring. LDL-Ccor levels fell below the thresholds of 5 mmol/L and 6.5 mmol/L (used in the DLCN scoring), in 38 and 40 of the Dutch FH cohort of 1504 patients, respectively (Supplementary Fig. 3). Table 2 shows the impact of LDL-Ccor levels on the clinical FH score in SNP-carriers. Among patients with genetically estimated elevated Lp(a), 30 patients (9.1%) were down-classified from DLCN category ‘possible FH’ to ‘unlikely FH’, of which 1 patient was found to carry a pathogenic FH variant (Table 2). An additional 26 patients were down-classified from DLCN category ‘probable FH’ to ‘possible FH’, yielding a total reclassification of 16.9% among SNP-carriers (Table 2 and Fig. 2). Supplementary Table 3 shows the results of a sensitivity analysis which assumed that a higher fraction of Lp(a) mass is measured as LDL-cholesterol (30% instead of 17%). In this case, 61 (18.4%) patients were down-classified from ‘possible FH’ to ‘unlikely FH’, of which 4 patients (6.6%) carried a pathogenic FH variant.
Table 2Proportion of patients per FH classification category, with and without use of Lp(a)-corrected LDL-C.
We next explored the contribution of Lp(a) to the prediction of ASCVD risk. Fig. 3 shows the reclassification of cardiovascular risk, with and without the addition of Lp(a) levels among all FH/M- SNP carriers of the Dutch FH cohort. Using the SCORE risk calculator, where the great majority of patients (189/229, 82.5%) was at low 10-year ASCVD mortality risk, 6/229 patients (2.6%) were reclassified into a higher risk category when Lp(a)-associated risk was taken into account. Using the SMART risk calculator, 12/66 (18.6%) of patients were classified into a higher risk category (Supplementary Table 4).
Fig. 3Reclassification of SMART and SCORE with and without Lp(a)-associated risk.
SCORE risk categories denote 10-year cardiovascular mortality risk: <5% was classified as low risk, 5–10% as moderate risk, and ≥10% as high risk. SMART risk categories denote risk of recurrent ASCVD events: <10% was classified as low, 10–20% as moderate, 20–30% as high, 30–40% as very high, and >40% as extremely high risk.
Using a genetic proxy to estimate Lp(a) levels in subjects referred for genetic testing for FH, we show that correcting LDL-cholesterol levels for Lp(a) results in downward reclassification of clinical FH categories, with 9% of referred patients not classifying for FH anymore. Moreover, we observed that addition of Lp(a) to ASCVD risk prediction resulted in 18.6% of patients being reclassified into a higher ASCVD risk category. We found that genetically estimated Lp(a) elevation, determined by the rs10455872 and rs3798220 SNP in LPA, was more prevalent among FH/M- than FH/M+ patients. These findings support an important role for Lp(a) measurement in all patients referred for genetic FH testing. Among those with genetically estimated high Lp(a), nearly 1 in 5 patients could be assigned a lower DLCN category after Lp(a) correction of LDL-cholesterol. Importantly, 30 (out of 331, 9.1%) patients were reclassified to the category “unlikely FH”, for which genetic analysis of FH genes is not routinely recommended.
Our findings are relevant given the fact that the question of performing genetic analyses may be reconsidered if patients are identified as having elevated Lp(a). Withholding molecular diagnostic testing for FH in this subgroup is important in light of both the burden for the patient, as well as the cost and time associated with genetic testing. In our Dutch FH cohort, we previously showed that in patients referred to our nationwide reference lab, no genetic confirmation of FH could be found in 85% of cases [
]. Thus, there is great potential for better pre-selection of clinical FH, for example by incorporating the Lp(a) level, prior to conducting a complete genetic analysis of dyslipidemia. It is important to note that, even though genetic analysis and possible cascade testing for an FH-variant may be withheld for some patients with high Lp(a), their families may still benefit from cascade testing for high Lp(a) [
Our finding that almost 1 out of 10 referred patients with genetically estimated high Lp(a) could be re-categorized to ‘unlikely FH’ after Lp(a)-correction of LDL-cholesterol, is in line with previous studies [
]. In an Australian FH cohort (n = 907), Chan et al. showed that Lp(a)-correction of LDL-cholesterol down-classified 5% (47/907) and 12% (40/330) of patients to ‘unlikely FH’, in the overall population and among those with elevated Lp(a) (>50 mg/dL), respectively. Importantly, none of these reclassified patients were shown to be carriers of an FH-variant [
]. Among 391 clinical FH patients from Canada, Trinder et al. showed that use of Lp(a)-adjusted LDL-cholesterol reclassified 6% (23/391) of patients to a lower DLCN category, but whether or not FH/M+ patients were amongst those classified to the ‘unlikely FH’ category was not reported [
]. Fatica et al. reported that among 31,215 samples submitted for advanced lipoprotein profiling, 11% of patients with measurable Lp(a)-cholesterol were reclassified to a lower DLCN LDL-cholesterol category [
]. In contrast, using data from the Copenhagen City Heart Study, Langsted et al. showed that 23% (765/3266) of patients with DLCN category ‘possible FH’ reclassified to ‘unlikely FH’ with use of Lp(a)-adjusted LDL-cholesterol [
]. This high percentage is likely explained by the fact that the study population was derived from the general population, rather than a pre-selected hospital population, and that considerably more patients had LDL-cholesterol levels close to the DLCN threshold value of 5 mmol/L. In light of clinical FH-reclassification, Lp(a) correction has the greatest relevance in patients with LDL-cholesterol levels that are borderline consistent with heterozygous FH: approximately between 5 and 6 mmol/L in adults.
We opted for a more conservative Lp(a) correction of LDL-cholesterol levels compared with aforementioned studies, assuming an average of 17.3% of Lp(a) mass, rather than 30%, is measured as LDL-cholesterol. Using this approach we showed that only 1 of the 30 patients who were reclassified to ‘unlikely FH’ was carrying an FH causing variant; which would have been missed if genetic testing was applied based on LDL-Ccor levels. The patient was a 26-year-old female with an untreated LDL-cholesterol level of 5.2 mmol/L (LDL-Ccor <5 mmol/L), who was found to be a heterozygous carrier of a missense LDLR variant. The fact that LDL-cholesterol levels are lower in FH patients at a young age may have predisposed this patient to ‘erroneous’ reclassification. We conducted a sensitivity analysis with a correction factor of 30%, and showed that this wrongly reclassified 4 of 61 patients to ‘unlikely FH’. In order not to miss heterozygous FH diagnoses, we propose to correct for a conservative estimation of Lp(a)-cholesterol, and in patients with clinically meaningful elevated Lp(a) levels only. Precise thresholds for which correction of Lp(a)-cholesterol is deemed acceptable remain to be established, and may depend of resource constraints for genetic FH-testing which vary between healthcare settings.
Besides the fact that high Lp(a) makes a genetic FH diagnosis less likely in a proportion of patients, identification of high Lp(a) is also important because it is an established risk factor for ASCVD [
]. The finding of an increased Lp(a) level may yet serve as an ASCVD risk enhancer and result in a decision to intensify therapy. We show that, among patients with genetically predicted high Lp(a), incorporation of Lp(a)-associated risk resulted in an increase in ASCVD risk category in up to 18% of patients. Our findings provide further support for the notion that Lp(a) should be measured once in adult life [
Our study has several limitations that warrant discussion. First, directly measured plasma Lp(a) levels were not available in our overall population because no plasma is stored after a referral for genetic analysis of dyslipidemia. Instead, we estimated Lp(a) levels in the overall Dutch FH cohort using a genetic instrument of LPA SNPs shown to be strongly correlated with measured Lp(a) levels. Since it is known that the association of LPA SNPs with Lp(a) levels may vary among different ethnic backgrounds [
], we measured Lp(a) levels in a subgroup which we re-invited for a study visit. Indeed, we validated that measured Lp(a) in SNP-carriers was elevated and closely resembled values derived from the UK Biobank used in our overall study population [
]. It is possible that some patients flagged by our genetic proxy have normal Lp(a) levels because the Lp(a)-raising effect is offset by other variants in the LPA gene [
Genome-wide association study and identification of a protective missense variant on lipoprotein(a) concentration: protective missense variant on lipoprotein(a) concentration - brief report.
Association of LPA variants with risk of coronary disease and the implications for lipoprotein(a)-lowering therapies: a mendelian randomization analysis.
], but their use was beyond the scope of our study. Although no data was available on ethnicity, our patients are derived from the general Dutch population that is mostly White. Our genetic instrument helps identify individuals with small Apo(a) isoforms and consequent high Lp(a) levels. It is known that subjects from African descent frequently have high Lp(a) in absence of a small Apo(a) isoform, so our genetic instrument would not perform equally well in this population [
Relationship of oxidized phospholipids on apolipoprotein B-100 particles to race/ethnicity, apolipoprotein(a) isoform size, and cardiovascular risk factors results from the dallas heart study.
]. Lastly, although our study was conducted in a large, nation-wide cohort of patients referred for FH-diagnostics, we included adult patients with treatment-naïve lipid panels only. Our results should therefore not be extrapolated to pediatric patients, nor to lipid panels obtained from patients while on lipid-lowering therapy.
In conclusion, using genetically estimated Lp(a) in a national FH cohort, we show that a considerable proportion of FH/M- patients have high Lp(a) and that correcting LDL-cholesterol levels for Lp(a)-cholesterol down-classified a clinically relevant proportion of patients to ‘unlikely FH’ for whom costly genetic testing could have been withheld. At the same time, Lp(a) had a clear impact on individual ASCVD risk prediction, with about 1 in 5 patients being classified to a higher cardiovascular risk category for whom more strict ASCVD risk management may thus be warranted. Taken together, our findings stress the importance of measuring Lp(a), because in patients with clinical FH this not only improves diagnostic yield of molecular FH-testing but also personalized ASCVD risk evaluation.
Author contributions
Tycho R. Tromp: contributed to the conception and design of the work., collected the data, analyzed the data and wrote the manuscript., Jorge Peter: collected the data, Linda Zuurbier: collected the data, Joep C. Defesche: collected the data, Laurens F. Reeskamp: contributed to the conception and design of the work. collected the data, G. Kees Hovingh: contributed to the conception and design of the work., Erik S.G. Stroes: contributed to the conception and design of the work. All authors provided critical revisions to the manuscript and gave final approval before submission.
Financial support
Research grants from the Netherlands Organization for Scientific Research (Vidi 016.156.445) and Klinkerpad fonds.
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
TRT, SI, JP, LZ and JCD declare no conflicts of interest.
NSN and LFR are co-founders of Lipid Tools.
GKH reports research grants from the Netherlands Organization for Scientific Research (vidi 016.156.445), CardioVascular Research Initiative, EU, and the Klinkerpad fonds; institutional research support from Aegerion, Amgen, AstraZeneca, Eli Lilly, Genzyme, Ionis, Kowa, Pfizer, Regeneron, Roche, Sanofi, and The Medicines Company; speaker's bureau and consulting fees from Amgen, Aegerion, Sanofi, and Regeneron until April 2019 (fees paid to the academic institution).
ESGS reports consulting fees from Amgen, Sanofi, Regeneron, Esperion, Novartis, Ionis/Akcea (all paid to the institution).
Acknowledgements
The authors thank the participants for their contribution to research. We thank Mrs. Kobie Los for collecting blood samples.
Appendix A. Supplementary data
The following is the Supplementary data to this article:
Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus Statement of the European Atherosclerosis Society.
Molecular genetic testing for autosomal dominant hypercholesterolemia in 29,449 Norwegian index patients and 14,230 relatives during the years 1993–2020.
Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study.
Association of LPA variants with risk of coronary disease and the implications for lipoprotein(a)-lowering therapies: a mendelian randomization analysis.
Relationship between “LDL-C” estimated true LDL-C, apolipoprotein B-100, and PCSK9 levels following lipoprotein(a) lowering with an antisense oligonucleotide.
Familial combined hyperlipidemia and hyperlipoprotein(a) as phenotypic mimics of familial hypercholesterolemia: frequencies, associations and predictions.
Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of medical genetics and Genomics and the association for molecular pathology.
Development and validation of a prediction rule for recurrent vascular events based on a cohort study of patients with arterial disease: the SMART risk score.
Genome-wide association study and identification of a protective missense variant on lipoprotein(a) concentration: protective missense variant on lipoprotein(a) concentration - brief report.
Relationship of oxidized phospholipids on apolipoprotein B-100 particles to race/ethnicity, apolipoprotein(a) isoform size, and cardiovascular risk factors results from the dallas heart study.
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