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Figure 1.  Flow Diagram of Analyses
Flow Diagram of Analyses

ASCVD indicates atherosclerotic cardiovascular disease; GRS, genetic risk score; Lp(a), lipoprotein(a); LDL-C, low-density lipoprotein cholesterol. To convert LDL-C to millimoles per liter, multiply by 0.0259; Lp(a) to milligrams per deciliter, divide by 2.4.

Figure 2.  Association of Measured Lipoprotein(a) (Lp[a]) and LPA Genetic Risk Score (GRS) With Incident Atherosclerotic Cardiovascular Disease (ASCVD) Among Individuals of White/European Ethnicity
Association of Measured Lipoprotein(a) (Lp[a]) and LPA Genetic Risk Score (GRS) With Incident Atherosclerotic Cardiovascular Disease (ASCVD) Among Individuals of White/European Ethnicity

The risk of incident ASCVD events is depicted as hazard ratios (HRs) and 95% confidence intervals for peripheral arterial disease (PAD), ischemic stroke, coronary artery disease (CAD), myocardial infarction (MI), cardiovascular disease (CVD) mortality, and composite ASCVD for 292 963 individuals not using cholesterol-lowering medication and without prevalent ASCVD at enrollment. Hazard ratios are scaled to depict a 120-nmol/L increase in measured Lp(a) or LPA genetic risk score (GRS) levels. All Cox proportional hazard models included age, sex, assessment center, genotyping batch, and the first 5 principal components of ancestry. Adj indicates adjusted.

Figure 3.  Association of Elevated LPA Genetic Risk Score (GRS) With Cardiovascular Risk When Individuals Are Matched for Measured Lipoprotein(a) (Lp[a]) Levels
Association of Elevated LPA Genetic Risk Score (GRS) With Cardiovascular Risk When Individuals Are Matched for Measured Lipoprotein(a) (Lp[a]) Levels

A, Crude time-to-first incident, composite atherosclerotic cardiovascular disease (ASCVD) event curves are shown for individuals with and without an elevated LPA GRS after matching for Lp(a) levels (matched LPA GRS-: predicted Lp(a) <120 nmol/L; matched LPA GRS+: predicted Lp(a) ≥120 nmol/L). B, The proportion of individuals with and without an elevated LPA GRS. C, Incidence rate of composite ASCVD events per 1000 person-years are displayed for 50-nmol/L bins of measured Lp(a) levels. Data points for incidence rates are displayed with the 95% confidence interval stratified by elevated LPA GRS cutoff levels of 120 nmol/L.

Table 1.  Enrollment Characteristics of UK Biobank Study Population
Enrollment Characteristics of UK Biobank Study Population
Table 2.  Additional Value of Lp(a) Metrics to Atherosclerotic Cardiovascular Disease Risk Prediction Among Individuals of European Ethnicity Defined by QRISK3 Using Complete and Imputed Dataa
Additional Value of Lp(a) Metrics to Atherosclerotic Cardiovascular Disease Risk Prediction Among Individuals of European Ethnicity Defined by QRISK3 Using Complete and Imputed Dataa
Supplement.

eMethods.

eTable 1. Genetic variants used in the LPA genetic risk score.

eTable 2. International Statistical Classification of Diseases and Related Health Problems (ICD) and Office of Population Censuses and Surveys Classification of Interventions and Procedures (OCPS) codes used to define atherosclerotic cardiovascular disease events.

eTable 3. Spearman's rank correlation between LPA genetic risk score and measured lipoprotein(a) levels for different ethnic groups.

eTable 4. Enrollment characteristics of UK Biobank study participants not using cholesterol-lowering medication and without prevalent atherosclerotic cardiovascular disease at study enrollment.

eTable 5. Risk discrimination models for incident atherosclerotic cardiovascular disease events for individuals of White/European and non-White/European ethnicity using cardiovascular risk calculators.

eTable 6. Additional value of lipoprotein(a) metrics to atherosclerotic cardiovascular disease risk discrimination among individuals of White/European ethnicity defined as borderline-to-intermediate risk by QRISK3 using only complete data.

eTable 7. Additional value of lipoprotein(a) metrics to atherosclerotic cardiovascular disease risk discrimination among individuals of White/European ethnicity defined by the Pooled Cohort Equations as borderline-intermediate risk using complete and imputed data.

eTable 8. Additional value of lipoprotein(a) metrics to atherosclerotic cardiovascular disease risk discrimination among individuals of White/European ethnicity defined by the Pooled Cohort Equations as borderline-intermediate risk using complete data.

eFigure 1. Self-reported ethnicity subgroups cluster with genetic principal components of ancestry.

eFigure 2. Distributions of measured lipoprotein(a) and LPA genetic risk scores.

eFigure 3. Association of measured lipoprotein(a) and LPA genetic risk score with risk of incident, composite atherosclerotic cardiovascular events.

eFigure 4. Measured lipoprotein(a) and LPA genetic risk score (GRS) associate with incident atherosclerotic cardiovascular disease among individuals of White/European ethnicity using cholesterol lowering medication.

eFigure 5. Measured lipoprotein(a) has stronger associations with composite atherosclerotic cardiovascular disease events at the extremes of elevated lipoprotein(a) than the LPA genetic score.

eFigure 6. Distributions of atherosclerotic cardiovascular disease risk determined by clinical risk calculators.

eReferences.

1.
Tsimikas  S.  A test in context: lipoprotein(a): diagnosis, prognosis, controversies, and emerging therapies.   J Am Coll Cardiol. 2017;69(6):692-711. doi:10.1016/j.jacc.2016.11.042PubMedGoogle ScholarCrossref
2.
Spence  JD, Koschinsky  M.  Mechanisms of lipoprotein(a) pathogenicity: prothrombotic, proatherosclerotic, or both?   Arterioscler Thromb Vasc Biol. 2012;32(7):1550-1551. doi:10.1161/ATVBAHA.112.251306PubMedGoogle ScholarCrossref
3.
van der Valk  FM, Bekkering  S, Kroon  J,  et al.  Oxidized Phospholipids on Lipoprotein(a) elicit arterial wall inflammation and an inflammatory monocyte response in humans.   Circulation. 2016;134(8):611-624. doi:10.1161/CIRCULATIONAHA.116.020838PubMedGoogle ScholarCrossref
4.
Boerwinkle  E, Leffert  CC, Lin  J, Lackner  C, Chiesa  G, Hobbs  HH.  Apolipoprotein(a) gene accounts for greater than 90% of the variation in plasma lipoprotein(a) concentrations.   J Clin Invest. 1992;90(1):52-60. doi:10.1172/JCI115855PubMedGoogle ScholarCrossref
5.
Clarke  R, Peden  JF, Hopewell  JC,  et al; PROCARDIS Consortium.  Genetic variants associated with Lp(a) lipoprotein level and coronary disease.   N Engl J Med. 2009;361(26):2518-2528. doi:10.1056/NEJMoa0902604PubMedGoogle ScholarCrossref
6.
Zekavat  SM, Ruotsalainen  S, Handsaker  RE,  et al; NHLBI TOPMed Lipids Working Group.  Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries.   Nat Commun. 2018;9(1):2606. doi:10.1038/s41467-018-04668-wPubMedGoogle ScholarCrossref
7.
Burgess  S, Ference  BA, Staley  JR,  et al; European Prospective Investigation Into Cancer and Nutrition–Cardiovascular Disease (EPIC-CVD) Consortium.  Association of LPA variants with risk of coronary disease and the implications for lipoprotein(a)-lowering therapies: a Mendelian randomization analysis.   JAMA Cardiol. 2018;3(7):619-627. doi:10.1001/jamacardio.2018.1470PubMedGoogle ScholarCrossref
8.
Larsson  SC, Gill  D, Mason  AM,  et al.  Lipoprotein(a) in Alzheimer, atherosclerotic, cerebrovascular, thrombotic, and valvular disease.   Circulation. 2020;141(22):1826-1828. doi:10.1161/CIRCULATIONAHA.120.045826PubMedGoogle ScholarCrossref
9.
Erqou  S, Kaptoge  S, Perry  PL,  et al; Emerging Risk Factors Collaboration.  Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality.   JAMA. 2009;302(4):412-423. doi:10.1001/jama.2009.1063PubMedGoogle ScholarCrossref
10.
Verbeek  R, Boekholdt  SM, Stoekenbroek  RM,  et al.  Population and assay thresholds for the predictive value of lipoprotein (a) for coronary artery disease: the EPIC-Norfolk Prospective Population Study.   J Lipid Res. 2016;57(4):697-705. doi:10.1194/jlr.P066258PubMedGoogle ScholarCrossref
11.
Nordestgaard  BG, Chapman  MJ, Ray  K,  et al; European Atherosclerosis Society Consensus Panel.  Lipoprotein(a) as a cardiovascular risk factor: current status.   Eur Heart J. 2010;31(23):2844-2853. doi:10.1093/eurheartj/ehq386PubMedGoogle ScholarCrossref
12.
Kamstrup  PR, Tybjaerg-Hansen  A, Steffensen  R, Nordestgaard  BG.  Genetically elevated lipoprotein(a) and increased risk of myocardial infarction.   JAMA. 2009;301(22):2331-2339.PubMedGoogle ScholarCrossref
13.
Arnett  DK, Blumenthal  RS, Albert  MA,  et al.  2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   Circulation. 2019;140(11):e596-e646.PubMedGoogle Scholar
14.
Tsimikas  S, Karwatowska-Prokopczuk  E, Gouni-Berthold  I,  et al; AKCEA-APO(a)-LRx Study Investigators.  Lipoprotein(a) reduction in persons with cardiovascular disease.   N Engl J Med. 2020;382(3):244-255. doi:10.1056/NEJMoa1905239PubMedGoogle ScholarCrossref
15.
Viney  NJ, van Capelleveen  JC, Geary  RS,  et al.  Antisense oligonucleotides targeting apolipoprotein(a) in people with raised lipoprotein(a): two randomised, double-blind, placebo-controlled, dose-ranging trials.   Lancet. 2016;388(10057):2239-2253. doi:10.1016/S0140-6736(16)31009-1PubMedGoogle ScholarCrossref
16.
Tsimikas  S, Viney  NJ, Hughes  SG,  et al.  Antisense therapy targeting apolipoprotein(a): a randomised, double-blind, placebo-controlled phase 1 study.   Lancet. 2015;386(10002):1472-1483. doi:10.1016/S0140-6736(15)61252-1PubMedGoogle ScholarCrossref
17.
Kamstrup  PR, Tybjærg-Hansen  A, Nordestgaard  BG.  Extreme lipoprotein(a) levels and improved cardiovascular risk prediction.   J Am Coll Cardiol. 2013;61(11):1146-1156. doi:10.1016/j.jacc.2012.12.023PubMedGoogle ScholarCrossref
18.
Lee  S-R, Prasad  A, Choi  Y-S,  et al.  LPA gene, ethnicity, and cardiovascular events.   Circulation. 2017;135(3):251-263. doi:10.1161/CIRCULATIONAHA.116.024611PubMedGoogle ScholarCrossref
19.
Gudbjartsson  DF, Thorgeirsson  G, Sulem  P,  et al.  Lipoprotein(a) concentration and risks of cardiovascular disease and diabetes.   J Am Coll Cardiol. 2019;74(24):2982-2994. doi:10.1016/j.jacc.2019.10.019PubMedGoogle ScholarCrossref
20.
Bycroft  C, Freeman  C, Petkova  D,  et al.  The UK Biobank resource with deep phenotyping and genomic data.   Nature. 2018;562(7726):203-209. doi:10.1038/s41586-018-0579-zPubMedGoogle ScholarCrossref
21.
Khera  AV, Everett  BM, Caulfield  MP,  et al.  Lipoprotein(a) concentrations, rosuvastatin therapy, and residual vascular risk: an analysis from the JUPITER Trial (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin).   Circulation. 2014;129(6):635-642. doi:10.1161/CIRCULATIONAHA.113.004406PubMedGoogle ScholarCrossref
22.
Willeit  P, Kiechl  S, Kronenberg  F,  et al.  Discrimination and net reclassification of cardiovascular risk with lipoprotein(a): prospective 15-year outcomes in the Bruneck Study.   J Am Coll Cardiol. 2014;64(9):851-860. doi:10.1016/j.jacc.2014.03.061PubMedGoogle ScholarCrossref
23.
Klarin  D, Zhu  QM, Emdin  CA,  et al; CARDIoGRAMplusC4D Consortium.  Genetic analysis in UK Biobank links insulin resistance and transendothelial migration pathways to coronary artery disease.   Nat Genet. 2017;49(9):1392-1397. doi:10.1038/ng.3914PubMedGoogle ScholarCrossref
24.
Therneau  TM. A Package for Survival Analysis in R. 2020. R package version 3.2-3. Accessed September 21, 2020. https://CRAN.R-project.org/package=survival
25.
Ho  DE, Imai  K, King  G, Stuart  EA.  MatchIt: nonparametric preprocessing for parametric causal inference.   J Stat Softw. 2011;42(8):1-28. doi:10.18637/jss.v042.i08Google ScholarCrossref
26.
Aragon  TJ. epitools: Epidemiology Tools. 2020. R package version 0.5-10.1. Accessed September 21, 2020. https://CRAN.R-project.org/package=epitools
27.
Goff  DC  Jr, Lloyd-Jones  DM, Bennett  G,  et al.  2013 ACC/AHA guideline on the assessment of cardiovascular risk.   J Am Coll Cardiol. 2014;63(25 Pt B):2935-2959. doi:10.1016/j.jacc.2013.11.005PubMedGoogle ScholarCrossref
28.
Grundy  SM, Stone  NJ, Bailey  AL,  et al.  2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on clinical practice guidelines.   J Am Coll Cardiol. 2019;73(24):e285-e350. doi:10.1016/j.jacc.2018.11.003PubMedGoogle ScholarCrossref
29.
Hippisley-Cox  J, Coupland  C, Vinogradova  Y, Robson  J, May  M, Brindle  P.  Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study.   BMJ. 2007;335(7611):136. doi:10.1136/bmj.39261.471806.55PubMedGoogle ScholarCrossref
30.
van Buuren  S, Groothuis-Oudshoorn  K.  Mice: multivariate imputation by chained qquations in R.   J Stat Softw. 2011;45(3):1-67.Google Scholar
31.
Robin  X, Turck  N, Hainard  A,  et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves.   BMC Bioinformatics. 2011;12(1):77. doi:10.1186/1471-2105-12-77PubMedGoogle ScholarCrossref
32.
Harrell  FE  Jr, Califf  RM, Pryor  DB, Lee  KL, Rosati  RA.  Evaluating the yield of medical tests.   JAMA. 1982;247(18):2543-2546. doi:10.1001/jama.1982.03320430047030PubMedGoogle ScholarCrossref
33.
Jenner  JL, Ordovas  JM, Lamon-Fava  S,  et al.  Effects of age, sex, and menopausal status on plasma lipoprotein(a) levels: the Framingham Offspring Study.   Circulation. 1993;87(4):1135-1141. doi:10.1161/01.CIR.87.4.1135PubMedGoogle ScholarCrossref
34.
Lanktree  MB, Anand  SS, Yusuf  S, Hegele  RA; SHARE Investigators.  Comprehensive analysis of genomic variation in the LPA locus and its relationship to plasma lipoprotein(a) in South Asians, Chinese, and European Caucasians.   Circ Cardiovasc Genet. 2010;3(1):39-46. doi:10.1161/CIRCGENETICS.109.907642PubMedGoogle ScholarCrossref
35.
Virani  SS, Brautbar  A, Davis  BC,  et al.  Associations between lipoprotein(a) levels and cardiovascular outcomes in black and white subjects: the Atherosclerosis Risk in Communities (ARIC) Study.   Circulation. 2012;125(2):241-249. doi:10.1161/CIRCULATIONAHA.111.045120PubMedGoogle ScholarCrossref
36.
Noureen  A, Fresser  F, Utermann  G, Schmidt  K.  Sequence variation within the KIV-2 copy number polymorphism of the human LPA gene in African, Asian, and European populations.   PLoS One. 2015;10(3):e0121582. doi:10.1371/journal.pone.0121582PubMedGoogle Scholar
37.
Khalifa  M, Noureen  A, Ertelthalner  K,  et al.  Lack of association of rs3798220 with small apolipoprotein(a) isoforms and high lipoprotein(a) levels in East and Southeast Asians.   Atherosclerosis. 2015;242(2):521-528. doi:10.1016/j.atherosclerosis.2015.07.015PubMedGoogle ScholarCrossref
38.
Paré  G, Çaku  A, McQueen  M,  et al; INTERHEART Investigators.  Lipoprotein(a) levels and the risk of myocardial infarction among 7 ethnic groups.   Circulation. 2019;139(12):1472-1482. doi:10.1161/CIRCULATIONAHA.118.034311PubMedGoogle ScholarCrossref
39.
Gupta  R, Vasisht  S, Bahl  VK, Wasir  HS.  Correlation of lipoprotein (a) to angiographically defined coronary artery disease in Indians.   Int J Cardiol. 1996;57(3):265-270. doi:10.1016/S0167-5273(96)02800-8PubMedGoogle ScholarCrossref
40.
Gambhir  JK, Kaur  H, Prabhu  KM, Morrisett  JD, Gambhir  DS.  Association between lipoprotein(a) levels, apo(a) isoforms and family history of premature CAD in young Asian Indians.   Clin Biochem. 2008;41(7-8):453-458. doi:10.1016/j.clinbiochem.2008.01.016PubMedGoogle ScholarCrossref
41.
Verbeek  R, Sandhu  MS, Hovingh  GK,  et al.  Lipoprotein(a) improves cardiovascular risk prediction based on established risk algorithms.   J Am Coll Cardiol. 2017;69(11):1513-1515. doi:10.1016/j.jacc.2017.01.017PubMedGoogle ScholarCrossref
42.
Di Angelantonio  E, Gao  P, Pennells  L,  et al; Emerging Risk Factors Collaboration.  Lipid-related markers and cardiovascular disease prediction.   JAMA. 2012;307(23):2499-2506.PubMedGoogle Scholar
43.
Mach  F, Baigent  C, Catapano  AL,  et al; ESC Scientific Document Group.  2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk.   Eur Heart J. 2020;41(1):111-188. doi:10.1093/eurheartj/ehz455PubMedGoogle ScholarCrossref
44.
Lloyd-Jones  DM.  Cardiovascular risk prediction: basic concepts, current status, and future directions.   Circulation. 2010;121(15):1768-1777. doi:10.1161/CIRCULATIONAHA.109.849166PubMedGoogle ScholarCrossref
45.
Suk Danik  J, Rifai  N, Buring  JE, Ridker  PM.  Lipoprotein(a), measured with an assay independent of apolipoprotein(a) isoform size, and risk of future cardiovascular events among initially healthy women.   JAMA. 2006;296(11):1363-1370. doi:10.1001/jama.296.11.1363PubMedGoogle ScholarCrossref
46.
Saleheen  D, Haycock  PC, Zhao  W,  et al.  Apolipoprotein(a) isoform size, lipoprotein(a) concentration, and coronary artery disease: a mendelian randomisation analysis.   Lancet Diabetes Endocrinol. 2017;5(7):524-533. doi:10.1016/S2213-8587(17)30088-8PubMedGoogle ScholarCrossref
47.
Langsted  A, Kamstrup  PR, Benn  M, Tybjærg-Hansen  A, Nordestgaard  BG.  High lipoprotein(a) as a possible cause of clinical familial hypercholesterolaemia: a prospective cohort study.   Lancet Diabetes Endocrinol. 2016;4(7):577-587. doi:10.1016/S2213-8587(16)30042-0PubMedGoogle ScholarCrossref
48.
Trinder  M, DeCastro  ML, Azizi  H,  et al.  Ascertainment bias in the association between elevated lipoprotein(a) and familial hypercholesterolemia.   J Am Coll Cardiol. 2020;75(21):2682-2693. doi:10.1016/j.jacc.2020.03.065PubMedGoogle ScholarCrossref
49.
Natarajan  P, Peloso  GM, Zekavat  SM,  et al; NHLBI TOPMed Lipids Working Group.  Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.   Nat Commun. 2018;9(1):3391. doi:10.1038/s41467-018-05747-8PubMedGoogle ScholarCrossref
Original Investigation
October 6, 2020

Clinical Utility of Lipoprotein(a) and LPA Genetic Risk Score in Risk Prediction of Incident Atherosclerotic Cardiovascular Disease

Author Affiliations
  • 1Centre for Heart Lung Innovation, The University of British Columbia, Vancouver, British Columbia, Canada
  • 2Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard, Cambridge, Massachusetts
  • 3Massachusetts General Hospital, Cardiology Division, Harvard Medical School, Boston, Massachusetts
  • 4Cardiovascular Research Center, Massachusetts General Hospital, Boston
  • 5Massachusetts General Hospital, Department of Medicine, Harvard Medical School, Boston
JAMA Cardiol. 2021;6(3):287-295. doi:10.1001/jamacardio.2020.5398
Key Points

Question  Does measurement of lipoprotein(a) and/or LPA genetic risk score (GRS) have clinical utility in risk prediction of incident atherosclerotic cardiovascular disease (ASCVD)?

Findings  In this cohort of 283 540 adults recruited by the UK Biobank, both measured lipoprotein(a) and LPA GRS were associated with comparable risk of incident ASCVD events. The LPA GRS did not yield additional prognostic information beyond measured lipoprotein(a), and both measured lipoprotein(a) and LPA GRS yielded modest improvements in the discrimination of ASCVD risk relative to the Pooled Cohort Equations or QRISK3.

Meaning  Cardiovascular risk assessment with lipoprotein(a) may be achieved with either direct measurement or an LPA GRS.

Abstract

Importance  Lipoprotein(a) is a highly heritable biomarker independently associated with atherosclerotic cardiovascular disease (ASCVD). It is unclear whether measured lipoprotein(a) or genetic factors associated with lipoprotein(a) can provide comparable or additional prognostic information for primary prevention.

Objective  To determine whether a genetic risk score (GRS) comprising 43 variants at the LPA gene, which encodes apolipoprotein(a), has clinical utility in assessing ASCVD risk compared with and in addition to lipoprotein(a) measurement.

Design, Setting, and Participants  The UK Biobank is a prospective observational study of approximately 500 000 volunteers aged 40 to 69 years who were recruited from 22 sites across the United Kingdom between 2006 and 2010. Using externally derived weights, an LPA GRS was calculated for 374 099 unrelated individuals with array-derived genotypes and lipoprotein(a) measures. Data were analyzed from April 2020 to March 2020.

Exposures  Measured lipoprotein(a) and LPA GRS.

Main Outcomes and Measures  We estimated the associations between measured lipoprotein(a) and LPA GRS with the incidence of ASCVD (peripheral arterial disease, coronary artery disease, myocardial infarction, ischemic stroke, and cardiovascular mortality) using Cox proportional hazards models. To determine the utility of using measured lipoprotein(a) and LPA GRS as risk enhancers for ASCVD, we assessed the potential improvement in ASCVD risk discrimination by QRISK3 and Pooled Cohort Equations among individuals with borderline to intermediate risk (n = 113 703 and 144 350, respectively).

Results  The mean age of the overall study population was 57.6 years, and 204 355 individuals were female (54.6%). During a median follow-up of 11.1 years (interquartile range, 1.4 years), 15 444 individuals developed an incident ASCVD event (5.1%). The LPA GRS explained approximately 60% of the variation in measured lipoprotein(a) for White/European individuals. Independently, both lipoprotein(a) and LPA GRS were associated with incident, composite ASCVD (hazard ratio per 120 nmol/L increase, 1.26; 95% CI, 1.23-1.28 vs hazard ratio, 1.29; 95% CI, 1.26-1.33; P < .001). The association between LPA GRS and ASCVD was substantially attenuated after adjusting for measured lipoprotein(a). Adding measured lipoprotein(a) or LPA GRS to QRISK3 provided modest improvements to the risk discrimination of incident ASCVD events (area under the receiver operating curve, 0.640; 95% CI, 0.633-0.647 vs 0.642; 95% CI, 0.635-0.649 for both; P = .005 and P = .01, respectively).

Conclusions and Relevance  When indicated, cardiovascular risk assessment with lipoprotein(a) at middle-age may include direct measurement or an LPA GRS.

Introduction

Lipoprotein(a) is a plasma lipoprotein composed of a low-density lipoprotein (LDL) particle that is covalently linked to apolipoprotein(a) by a disulfide bond. On an equimolar basis, lipoprotein(a) is more atherogenic than LDL because the additional apolipoprotein(a) component may exacerbate atherothrombosis by promoting vascular inflammation and its potential antifibrinolytic activity is associated with inhibition of plasminogen.1-3 Lipoprotein(a) levels are 75% to 95% heritable and predominately determined by single-nucleotide variants at the LPA gene and copy number variants specifically in the kringle IV type 2 domain.4-6 Genetic association studies have identified genetic variants explaining approximately 60% of the variability in lipoprotein(a) levels in European populations.7,8 Elevated lipoprotein(a), defined as lipoprotein(a) level of 120 nmol/L or greater or approximately 50 mg/dL, is common and varies in prevalence by ancestry (affects 1 in 5 European individuals).9-12

Mendelian randomization studies7,13 suggest that lipoprotein(a) is a causal contributor to ASCVD,7,13 and ongoing randomized clinical trials are testing this hypothesis.14-16 Both the diagnostic yield and clinical value of genetic testing of LPA are not well understood. Specifically, unlike LDL cholesterol, it remains unclear whether genetic factors related to lipoprotein(a) may provide information regarding lifetime exposure relevant to ASCVD risk prediction and selection of patients for primary prevention with statin therapy.4,17-19

Here, we report our investigation of the prognostic utility of testing for the genetic determinants of lipoprotein(a) relative to direct measurement of lipoprotein(a) levels in a large cohort of middle- to late-age adults not using lipid-lowering medication and without baseline ASCVD.

Methods
UK Biobank Cohort

The UK Biobank is a prospective observational study of approximately 500 000 volunteer adults aged 40 to 69 years recruited from 22 sites across the United Kingdom between 2006 and 2010, with follow-up ongoing. This study included individuals of third-degree relatedness or less (Figure 1).20 Biochemical measurements, physical examination measurements, and medical histories were assessed at the time of study enrollment. Self-reported ethnicities were categorized as mixed, African/Black, European/White, East Asian, South Asian, and unknown.

The UK Biobank protocol was approved by the Northwest Multi-Center Research Ethics Committee, and all study participants provided written informed consent. Secondary use of data for this study was approved by the Massachusetts General Hospital institutional review board 2013P001840.

Lipoprotein(a) Measurement

Lipoprotein(a) was measured in nanomoles per liter at study enrollment using an immunoturbidimetric method on the Beckman Coulter AU5800 platform (Randox Bioscience, UK), which is isoform insensitive.10 To convert lipoprotein(a) values to milligrams per deciliter, divide by 2.15.

LPA Genetic Risk Score

We used genotyping array data from UK Biobank participants to calculate a previously described weighted LPA genetic risk score (GRS), composed of 43 single-nucleotide variants that were conditionally and significantly associated with lipoprotein(a) levels in data sets external to the UK Biobank (eTable 1 and eMethods in the Supplement).7 The units of the LPA GRS were converted from milligrams per deciliter to nanomoles per liter by multiplying by 2.15 to harmonize units with the measured lipoprotein(a).21 An LPA GRS of at least 120 was considered elevated.7,8,11,12,17,22

Atherosclerotic Cardiovascular Disease Outcomes

The outcomes of myocardial infarction, coronary artery disease, ischemic stroke, peripheral arterial disease, cardiovascular mortality, and a composite of the aforementioned outcomes were based on International Statistical Classification of Diseases and Related Health Problems and Office of Population Censuses and Surveys Classification of Interventions and Procedures codes (eTable 2 in the Supplement).23 Incident events were defined as the first event occurring between the date of enrollment and the end of follow-up of March 31, 2020. Individuals were censored at death or loss to follow-up. Individuals reporting use of cholesterol-lowering medication or prevalent angina, coronary artery disease, history of myocardial infarction, history of stroke, or peripheral arterial disease/revascularization at study enrollment were excluded from analyses of incident events. A sensitivity analysis was performed with individuals without prevalent ASCVD but using cholesterol-lowering medication.

Statistical Analyses

Analyses were performed using R, version 4.0.0 (R Core Team [2020]). The association between LPA GRS and measured lipoprotein(a) levels were assessed by Spearman correlation and adjusted linear regression models (covariates of age, sex, assessment center, genotyping batch, and the first 5 principal components of ancestry).

We assessed the risk of incident ASCVD events Cox proportional hazards models with the covariates of sex, age, assessment center, genotyping batch, and the first 5 principal components of ancestry using the survival package (version 3.1-12).24 When explicitly stated, Cox proportional hazards models included the additional covariate of continuous, measured lipoprotein(a) or LPA GRS.

To compare whether an elevated LPA GRS was associated with greater risk of ASCVD for a given lipoprotein(a) level, individuals with and without an elevated LPA GRS were matched at a 1:1 ratio based on measured lipoprotein(a) levels using the nearest neighbor algorithm from the MatchIt, version 3.0.2 (R Core Team [2020]), package with a caliper set to 0.02.25 Measured lipoprotein(a) levels were compared between matched individuals with and without an elevated LPA GRS using a Mann-Whitney U test. The risks of incident ASCVD events were compared between matched individuals with and without an elevated LPA GRS using a log-rank test.

We calculated the incidence rates for composite ASCVD events for each percentile of measured lipoprotein(a) and LPA GRS using the Poisson rate exact method from the epitools package, version 0.5-10.1.26 Additionally, for individuals with and without an elevated LPA GRS (≥120 nmol/L), we calculated the incidence rates for composite ASCVD events for percentiles of measured lipoprotein(a) and LPA GRS or for 50 nmol/L bins of measured lipoprotein(a) levels with the maximum lipoprotein(a) bin was set to lipoprotein(a) levels 250 nmol/L or greater.

Lastly, we assessed whether lipoprotein(a) levels and/or LPA GRS could refine the ASCVD risk discrimination for individuals without diabetes or severe hypercholesterolemia (LDL cholesterol level ≥190 mg/dL; to convert to millimoles per liter, multiply by 0.0259) classified as borderline-intermediate risk by the Pooled Cohort Equations27,28 and QRISK3,29 respectively (predicted 10-year ASCVD risk: 5%-20%). This borderline-intermediate risk group consists of individuals in whom statin therapy could be warranted if risk enhancers are present for a given patient (ie, elevated lipoprotein[a]).27,28 We used multiple imputation by chained equations to impute missing values needed to calculate ASCVD risk according to the Pooled Cohort Equations and QRISK3 with the mice package, version 3.11.0 (The R Foundation).30 The associations between continuous, measured lipoprotein(a) levels, LPA GRS, and Pooled Cohort Equations–derived or QRISK3-derived clinical risk scores27 with incident myocardial infarction, ischemic stroke, or cardiovascular mortality were assessed by the area under the curve from receiver operating characteristic models31 and the Harrell C statistic32 from Cox proportional hazards models. We assessed whether Cox proportional hazards models and correlated receiver operating characteristic curves were statistically different using an analysis of variance test and Delong test, respectively. Statistical significance was claimed when 2-sided P values were less than .05.

Results
Cohort Characteristics

A flowchart of the subgroups used in this study is shown in Figure 1. For the overall study population of 374 099 individuals, the mean (SD) age at study enrollment was 57.6 (8.0) years, and 204 355 individuals were female (54.6%; Table 1). The distributions of measured lipoprotein(a), LPA GRS, and the residual of measured vs LPA GRS-expected lipoprotein(a) for these individuals are shown across strata of ethnicity in eFigures 1 and 2 in the Supplement. The LPA GRS was associated with measured levels of lipoprotein(a) for White/European individuals (R2 = 0.595; P < .001), South Asians (R2 = 0.11; P < .001), East Asian individuals (R2 = 0.078; P < .001), and Black/African individuals (R2 = 0.038; P = .03). The Pearson correlation coefficient between the LPA GRS and measured lipoprotein(a) levels was 0.717 for White/European individuals, 0.371 for South Asian individuals, 0.281 for East Asian individuals, and 0.070 for Black/African individuals (eTable 3 in the Supplement).

For 300 839 individuals without prevalent ASCVD and not using cholesterol-lowering medication, the mean (SD) age at study enrollment was 56.6 (8.0) years, and 174 555 individuals were female (58.0%). The median level of lipoprotein(a) was 24.1 nmol/L (interquartile range, 73.6 nmol/L) and the median length of follow-up for composite ASCVD events was 11.1 years (interquartile range, 1.4 years; eTable 4 in the Supplement). A 120-nmol/L increase in measured lipoprotein(a) was significantly associated with increased risk of incident, composite ASCVD events for White/European individuals (hazard ratio [HR], 1.25; 95% CI, 1.23-1.27; P = 3.71 × 10−71), South Asian individuals (HR, 1.24; 95% CI, 1.03-1.44; P = .04), East Asian individuals (HR, 1.76; 95% CI, 1.27-2.25; P = .02), and mixed individuals (HR, 1.39; 95% CI, 1.06-1.71; P = .05), but not Black/African individuals (HR, 1.06; 95% CI, 0.84-1.30; P = .58) or individuals of unknown ethnicity (HR, 1.11; 95% CI, 0.84-1.40 P = .44; eFigure 3 in the Supplement). For statistical power and predictive strength, we focused subsequent analyses on individuals of White/European ethnicity (Figure 1).

Association of Measured Lipoprotein(a) and LPA GRS With Atherosclerotic Cardiovascular Diseases

For individuals of White/European ethnicity without prevalent ASCVD and not using cholesterol-lowering medication (n = 283 540), a 120-nmol/L increase in either measured lipoprotein(a) or LPA GRS was associated with increased risk of incident peripheral arterial disease (HR, 1.25; 95% CI, 1.19-1.31 and 1.34; 95% CI, 1.26-1.42), coronary artery disease (HR, 1.40; 95% CI, 1.37-1.43 and 1.45; 95% CI, 1.41-1.50), myocardial infarction (HR, 1.32; 95% CI, 1.28-1.36 vs 1.38, 95% CI, 1.33-1.43), ischemic stroke (HR, 1.11; 95% CI, 1.05-1.16 and 1.12, 95% CI, 1.04-1.19), and cardiovascular mortality (HR, 1.09; 95% CI, 1.04-1.16 and 1.09, 95% CI, 1.02-1.16; Figure 2). In a sensitivity analysis of individuals of White/European ethnicity without prevalent ASCVD but using cholesterol-lowering medication (n = 43 829), the effect estimates for the association between lipoprotein(a) and risk of incident ASCVD were modestly attenuated (eFigure 4 in the Supplement). Notably, the risk of incident, composite ASCVD events and probability of ASCVD by age 75 years was more pronounced at the extremes of measured lipoprotein(a) than LPA GRS (eFigure 5 in the Supplement).

Using LPA GRS for Cardiovascular Disease Risk Prediction Compared With Measured Lipoprotein(a) Levels

The associations between LPA GRS and risk of incident peripheral arterial disease, coronary artery disease, myocardial infarction, ischemic stroke, cardiovascular mortality, and composite ASCVD were substantially attenuated when models were additionally adjusted for measured lipoprotein(a) levels (Figure 2). Additionally, to assess the association of an elevated LPA GRS with ASCVD risk at comparable levels of measured lipoprotein(a), we matched individuals of White/European ethnicity with and without an elevated LPA GRS (≥120 nmol/L) based on measured lipoprotein(a). Measured lipoprotein(a) levels were comparable between matched individuals with and without elevated LPA GRS (median, 149.2 nmol/L; interquartile range, 74.3 nmol/L vs median, 149.1 nmol/L; interquartile range, 74.0 nmol/L; Mann-Whitney P = .56). There was no significant difference in the risk of an incident, composite ASCVD events between individuals with and without an elevated LPA GRS matched for lipoprotein(a) levels (log-rank P = .60; Figure 3A).

To further explore the influence of an elevated LPA GRS on risk of ASCVD at comparable levels of lipoprotein(a), we assessed the incidence rate of composite ASCVD events across 50-nmol/L bins of measured lipoprotein(a) for individuals of White/European ethnicity with and without an elevated LPA GRS (≥120 nmol/L). In general, there was a trend toward increased incidence rate of ASCVD with increasing bins of lipoprotein(a) levels for both individuals with and without an elevated LPA GRS. However, for each elevated LPA GRS threshold, an elevated lipoprotein(a) GRS did not significantly associate with a greater incidence rate of ASCVD compared with a nonelevated LPA GRS within a given bin of measured lipoprotein(a) (Figure 3B and C).

Lipoprotein(a) and Improvement in Risk Discrimination Among Borderline-Intermediate Risk Patients

The distribution of QRISK3 and Pooled Cohort Equations 10-year ASCVD risk scores for the 300 839 individuals of European and non-European ethnicity not using cholesterol-lowering medication and without prevalent ASCVD at enrollment are displayed in eFigure 6 in the Supplement. Prediction with QRISK3 had significantly greater ASCVD risk discrimination compared with the Pooled Cohort Equations for these individuals (eTable 5 in the Supplement). We used a subgroup of 113 703 and 144 350 individuals of White/European ethnicity defined as borderline to intermediate ASCVD risk by the Pooled Cohort Equation and QRISK3 to assess the role of measured lipoprotein(a) and LPA GRS as a risk enchancer.12,27 Adding continuous, measured lipoprotein(a) levels to QRISK3 provided modest improvements to the predicted risk of incident ASCVD events as assessed by AUROC and Harrell C statistic (Table 2). The AUROC improved from 0.640 (95% CI, 0.633-0.647) to 0.642 (95% CI, 0.634-0.649) and 0.642 (95% CI, 0.634-0.649) when measured, continuous lipoprotein(a) levels and LPA GRS were added to QRISK3 (P = .005 and P = .01, respectively). Similar results were observed when continuous, measured lipoprotein(a) was added to the Pooled Cohort Equations and when analyses were restricted to only individuals with complete clinical data (no imputation and exclusion of individuals with missing data; eTables 6-8 in the Supplement).

Discussion

Here we used the UK Biobank cohort to demonstrate that measured lipoprotein(a) and an LPA GRS are associated with increased risk of incident ASCVD in a primary prevention setting. The major advance from this study is the demonstration that an LPA GRS offered comparable ASCVD risk prediction to directly measured lipoprotein(a). In a large observational cohort, we observed that increased lipoprotein(a) is independently associated with future risk for ASCVD but with modest discrimination in addition to clinical risk scores at the level of population screening for primary prevention.

In contrast to LDL cholesterol, this work suggests that profiling the genetic determinants of plasma lipoprotein(a) does not provide additional value to measured levels of lipoprotein(a) in terms of ASCVD risk prediction. These data suggest that the LPA GRS is likely not a better marker for exposure to lipoprotein(a) than an isolated lipoprotein(a) measurement. We suspect that this is explained by 2 key factors: (1) lipoprotein(a) displays higher heritability than LDL cholesterol levels, and (2) lipoprotein(a) levels are generally much more stable throughout life compared with other circulating lipoproteins (ie, minimal influence of age, sex, genetic factors outside the LPA gene, environmental factors, or currently available medicines).33 The polygenic architecture of complex traits, such as lipoprotein(a), have shown variable transferability across genetic ancestries as demonstrated in this study and others.4,18,34-37 Elevated lipoprotein(a) is strongly associated with ASCVD risk among multiple ethnic groups, and lipoprotein(a) levels greater than 120 nmol/L are observed in 1 of 4 African individuals, 1 in 10 South and South East Asian individuals, 1 in 10 Arab individuals, 1 in 7 Latin American individuals, and 1 in 5 European individuals.35,38-40 We observed that risk prediction performance for LPA GRS and measured lipoprotein(a) varies similarly across ethnicities.

Our findings are in accordance with other studies demonstrating that adding continuous lipoprotein(a) levels to clinical risk scores leads to modest improvements in risk discrimination for ASCVD.22,41,42 While some guidelines support broad population-based screening with lipoprotein(a),43 the small improvement in the C statistics relative to clinical risk scores (Δ C statistic of approximately 0.002) suggests that measured lipoprotein(a) or LPA GRS may be an inefficient approach for refinement of ASCVD risk among asymptomatic middle-aged adults broadly.44 However, because lipoprotein(a) levels display an extremely right-skewed distribution in the general population (potentially varying more than 1000-fold between individuals, approximately 0.2 to ≥200 mg/dL), individuals with extreme lipoprotein(a) levels greater than 200 mg/dL could have a 3- to 4-fold increased lifetime risk of ASCVD.7,13,17,45 In such cases, the modest improvement in ASCVD risk discrimination that was observed in this study when continuous levels of measured lipoprotein(a) or LPA GRS were added to clinical risk scores may underestimate cardiovascular risk. Inclusion of the entire range of lipoprotein(a) levels in ASCVD risk discrimination and reclassification models often fails to accurately quantify the cardiovascular risk associated with the extremes of elevated lipoprotein(a) (ie, because extremely elevated lipoprotein[a] is rare there is limited predictive power).17,41 Efficient strategies to identify individuals with extremely elevated lipoprotein(a) levels require further research.

Previous studies suggest that small apolipoprotein(a) isoforms, which are also associated with higher lipoprotein(a) levels, may increase an individual’s risk of ASCVD more than expected by changes in lipoprotein(a) concentration alone.46 However, in this study we did not find that the LPA GRS, which contains several genetic variants associated with small apolipoprotein(a) size,6 explained additional ASCVD risk beyond measured levels of lipoprotein(a). Unlike isoform-independent lipoprotein(a) molar concentration, the associations of apolipoprotein(a), and by extension isoform-dependent measurements, with ASCVD may be confounded by pleiotropic effects on high-density lipoprotein cholesterol and triglycerides.19 In some cases, the genetic determinants of elevated lipoprotein(a) may help discern the familial risk of lipoprotein(a)-associated ASCVD that is not always conclusive from lipoprotein(a) measurement alone. For instance, a single copy of the rs10455872-G allele, which is common in European populations, is known to associate with extremely elevated lipoprotein(a) that can present phenotypically similar to familial hypercholesteremia and thus may be amenable to cascade screening.47,48

Limitations

First, a major limitation of this study is that it focused on individuals of White/European ethnicity, and the generalizability of these findings, in particular the LPA GRS, to other ethnic groups requires further research. Notably, we show that the association of measured lipoprotein(a) with incident ASCVD risk may vary between ethnic groups and that, similar to other GRSs, the LPA GRS performed suboptimally in non–White/European ethnicities. An LPA GRS needs to be developed and tested in non–White/European cohorts to determine whether these findings extend to individuals of other ethnic groups. Second, most individuals enrolled in this study were recruited at middle age (mean [SD], 56.8 [8.0] years), with median follow-up of 11.1 years, and thus the influence of measured lipoprotein(a) and LPA GRS on incident premature and lifelong ASCVD risk remains to be determined in prospective primary prevention cohorts with younger age of enrollment and longer follow-up. Third, additional limitations include the ascertainment bias associated with volunteer recruitment, use of hospitalization and operation codes to define ASCVD events, and that the LPA GRS was constructed with winsorization (lipoprotein[a] levels greater than 130 mg/dL were set to 130 mg/dL), which may fail to explain some of the genetic variation associated with extremely elevated levels of measured lipoprotein(a).7 Despite this, the LPA GRS is still a reasonable genetic predictor that explains greater than 60% of the variation in lipoprotein(a) levels, an association that is considerably greater than contemporary GRSs for other lipid traits such as LDL cholesterol.49

Conclusions

In conclusion, the results from this study suggest that an LPA GRS provides comparable risk prediction for incident ASCVD compared with measured lipoprotein(a). Measured lipoprotein(a) and the LPA GRS both provided modest improvement in risk discrimination beyond guideline-supported risk scores, which supports the role of lipoprotein(a) as a risk-enhancing factor.

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Article Information

Corresponding Author: Pradeep Natarajan, MD, MMSc, Massachusetts General Hospital, 185 Cambridge St, CPZN 3.184, Boston, MA 02114 (pnatarajan@mgh.harvard.edu).

Accepted for Publication: September 15, 2020.

Published Online: October 6, 2020. doi:10.1001/jamacardio.2020.5398

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Trinder M et al. JAMA Cardiology.

Author Contributions: Mr Trinder and Dr Natarajan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Trinder, Aragam, Natarajan.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Trinder, Natarajan.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Trinder, Uddin, Aragam, Natarajan.

Obtained funding: Aragam, Natarajan.

Administrative, technical, or material support: Trinder, Finneran, Aragam, Natarajan.

Supervision: Aragam, Natarajan.

Conflict of Interest Disclosures: Dr Natarajan reported grants from Amgen during the conduct of the study and grants from Boston Scientific; grants and personal fees from Apple; personal fees from Novartis and Blackstone Life Sciences; and other support from Vertex outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported by UK Biobank application 7089. Dr Natarajan is supported by grants from the National Heart, Lung, and Blood Institute (R01HL142711, R01HL148565, R01HL148050), Fondation Leducq (TNE-18CVD04), and a Hassenfeld Scholar Award from the Massachusetts General Hospital. Amgen Inc (Thousand Oaks, California) funded this study.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Meeting Presentation: This paper was presented at the European Atherosclerosis Congress; October 6, 2020; virtual conference.

Additional Contributions: We thank the participants and individuals involved in establishing the UK Biobank project and others for establishing the computational resources, tools, and support for this project. The UK Biobank analyses were performed using application 7089.

References
1.
Tsimikas  S.  A test in context: lipoprotein(a): diagnosis, prognosis, controversies, and emerging therapies.   J Am Coll Cardiol. 2017;69(6):692-711. doi:10.1016/j.jacc.2016.11.042PubMedGoogle ScholarCrossref
2.
Spence  JD, Koschinsky  M.  Mechanisms of lipoprotein(a) pathogenicity: prothrombotic, proatherosclerotic, or both?   Arterioscler Thromb Vasc Biol. 2012;32(7):1550-1551. doi:10.1161/ATVBAHA.112.251306PubMedGoogle ScholarCrossref
3.
van der Valk  FM, Bekkering  S, Kroon  J,  et al.  Oxidized Phospholipids on Lipoprotein(a) elicit arterial wall inflammation and an inflammatory monocyte response in humans.   Circulation. 2016;134(8):611-624. doi:10.1161/CIRCULATIONAHA.116.020838PubMedGoogle ScholarCrossref
4.
Boerwinkle  E, Leffert  CC, Lin  J, Lackner  C, Chiesa  G, Hobbs  HH.  Apolipoprotein(a) gene accounts for greater than 90% of the variation in plasma lipoprotein(a) concentrations.   J Clin Invest. 1992;90(1):52-60. doi:10.1172/JCI115855PubMedGoogle ScholarCrossref
5.
Clarke  R, Peden  JF, Hopewell  JC,  et al; PROCARDIS Consortium.  Genetic variants associated with Lp(a) lipoprotein level and coronary disease.   N Engl J Med. 2009;361(26):2518-2528. doi:10.1056/NEJMoa0902604PubMedGoogle ScholarCrossref
6.
Zekavat  SM, Ruotsalainen  S, Handsaker  RE,  et al; NHLBI TOPMed Lipids Working Group.  Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries.   Nat Commun. 2018;9(1):2606. doi:10.1038/s41467-018-04668-wPubMedGoogle ScholarCrossref
7.
Burgess  S, Ference  BA, Staley  JR,  et al; European Prospective Investigation Into Cancer and Nutrition–Cardiovascular Disease (EPIC-CVD) Consortium.  Association of LPA variants with risk of coronary disease and the implications for lipoprotein(a)-lowering therapies: a Mendelian randomization analysis.   JAMA Cardiol. 2018;3(7):619-627. doi:10.1001/jamacardio.2018.1470PubMedGoogle ScholarCrossref
8.
Larsson  SC, Gill  D, Mason  AM,  et al.  Lipoprotein(a) in Alzheimer, atherosclerotic, cerebrovascular, thrombotic, and valvular disease.   Circulation. 2020;141(22):1826-1828. doi:10.1161/CIRCULATIONAHA.120.045826PubMedGoogle ScholarCrossref
9.
Erqou  S, Kaptoge  S, Perry  PL,  et al; Emerging Risk Factors Collaboration.  Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality.   JAMA. 2009;302(4):412-423. doi:10.1001/jama.2009.1063PubMedGoogle ScholarCrossref
10.
Verbeek  R, Boekholdt  SM, Stoekenbroek  RM,  et al.  Population and assay thresholds for the predictive value of lipoprotein (a) for coronary artery disease: the EPIC-Norfolk Prospective Population Study.   J Lipid Res. 2016;57(4):697-705. doi:10.1194/jlr.P066258PubMedGoogle ScholarCrossref
11.
Nordestgaard  BG, Chapman  MJ, Ray  K,  et al; European Atherosclerosis Society Consensus Panel.  Lipoprotein(a) as a cardiovascular risk factor: current status.   Eur Heart J. 2010;31(23):2844-2853. doi:10.1093/eurheartj/ehq386PubMedGoogle ScholarCrossref
12.
Kamstrup  PR, Tybjaerg-Hansen  A, Steffensen  R, Nordestgaard  BG.  Genetically elevated lipoprotein(a) and increased risk of myocardial infarction.   JAMA. 2009;301(22):2331-2339.PubMedGoogle ScholarCrossref
13.
Arnett  DK, Blumenthal  RS, Albert  MA,  et al.  2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   Circulation. 2019;140(11):e596-e646.PubMedGoogle Scholar
14.
Tsimikas  S, Karwatowska-Prokopczuk  E, Gouni-Berthold  I,  et al; AKCEA-APO(a)-LRx Study Investigators.  Lipoprotein(a) reduction in persons with cardiovascular disease.   N Engl J Med. 2020;382(3):244-255. doi:10.1056/NEJMoa1905239PubMedGoogle ScholarCrossref
15.
Viney  NJ, van Capelleveen  JC, Geary  RS,  et al.  Antisense oligonucleotides targeting apolipoprotein(a) in people with raised lipoprotein(a): two randomised, double-blind, placebo-controlled, dose-ranging trials.   Lancet. 2016;388(10057):2239-2253. doi:10.1016/S0140-6736(16)31009-1PubMedGoogle ScholarCrossref
16.
Tsimikas  S, Viney  NJ, Hughes  SG,  et al.  Antisense therapy targeting apolipoprotein(a): a randomised, double-blind, placebo-controlled phase 1 study.   Lancet. 2015;386(10002):1472-1483. doi:10.1016/S0140-6736(15)61252-1PubMedGoogle ScholarCrossref
17.
Kamstrup  PR, Tybjærg-Hansen  A, Nordestgaard  BG.  Extreme lipoprotein(a) levels and improved cardiovascular risk prediction.   J Am Coll Cardiol. 2013;61(11):1146-1156. doi:10.1016/j.jacc.2012.12.023PubMedGoogle ScholarCrossref
18.
Lee  S-R, Prasad  A, Choi  Y-S,  et al.  LPA gene, ethnicity, and cardiovascular events.   Circulation. 2017;135(3):251-263. doi:10.1161/CIRCULATIONAHA.116.024611PubMedGoogle ScholarCrossref
19.
Gudbjartsson  DF, Thorgeirsson  G, Sulem  P,  et al.  Lipoprotein(a) concentration and risks of cardiovascular disease and diabetes.   J Am Coll Cardiol. 2019;74(24):2982-2994. doi:10.1016/j.jacc.2019.10.019PubMedGoogle ScholarCrossref
20.
Bycroft  C, Freeman  C, Petkova  D,  et al.  The UK Biobank resource with deep phenotyping and genomic data.   Nature. 2018;562(7726):203-209. doi:10.1038/s41586-018-0579-zPubMedGoogle ScholarCrossref
21.
Khera  AV, Everett  BM, Caulfield  MP,  et al.  Lipoprotein(a) concentrations, rosuvastatin therapy, and residual vascular risk: an analysis from the JUPITER Trial (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin).   Circulation. 2014;129(6):635-642. doi:10.1161/CIRCULATIONAHA.113.004406PubMedGoogle ScholarCrossref
22.
Willeit  P, Kiechl  S, Kronenberg  F,  et al.  Discrimination and net reclassification of cardiovascular risk with lipoprotein(a): prospective 15-year outcomes in the Bruneck Study.   J Am Coll Cardiol. 2014;64(9):851-860. doi:10.1016/j.jacc.2014.03.061PubMedGoogle ScholarCrossref
23.
Klarin  D, Zhu  QM, Emdin  CA,  et al; CARDIoGRAMplusC4D Consortium.  Genetic analysis in UK Biobank links insulin resistance and transendothelial migration pathways to coronary artery disease.   Nat Genet. 2017;49(9):1392-1397. doi:10.1038/ng.3914PubMedGoogle ScholarCrossref
24.
Therneau  TM. A Package for Survival Analysis in R. 2020. R package version 3.2-3. Accessed September 21, 2020. https://CRAN.R-project.org/package=survival
25.
Ho  DE, Imai  K, King  G, Stuart  EA.  MatchIt: nonparametric preprocessing for parametric causal inference.   J Stat Softw. 2011;42(8):1-28. doi:10.18637/jss.v042.i08Google ScholarCrossref
26.
Aragon  TJ. epitools: Epidemiology Tools. 2020. R package version 0.5-10.1. Accessed September 21, 2020. https://CRAN.R-project.org/package=epitools
27.
Goff  DC  Jr, Lloyd-Jones  DM, Bennett  G,  et al.  2013 ACC/AHA guideline on the assessment of cardiovascular risk.   J Am Coll Cardiol. 2014;63(25 Pt B):2935-2959. doi:10.1016/j.jacc.2013.11.005PubMedGoogle ScholarCrossref
28.
Grundy  SM, Stone  NJ, Bailey  AL,  et al.  2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on clinical practice guidelines.   J Am Coll Cardiol. 2019;73(24):e285-e350. doi:10.1016/j.jacc.2018.11.003PubMedGoogle ScholarCrossref
29.
Hippisley-Cox  J, Coupland  C, Vinogradova  Y, Robson  J, May  M, Brindle  P.  Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study.   BMJ. 2007;335(7611):136. doi:10.1136/bmj.39261.471806.55PubMedGoogle ScholarCrossref
30.
van Buuren  S, Groothuis-Oudshoorn  K.  Mice: multivariate imputation by chained qquations in R.   J Stat Softw. 2011;45(3):1-67.Google Scholar
31.
Robin  X, Turck  N, Hainard  A,  et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves.   BMC Bioinformatics. 2011;12(1):77. doi:10.1186/1471-2105-12-77PubMedGoogle ScholarCrossref
32.
Harrell  FE  Jr, Califf  RM, Pryor  DB, Lee  KL, Rosati  RA.  Evaluating the yield of medical tests.   JAMA. 1982;247(18):2543-2546. doi:10.1001/jama.1982.03320430047030PubMedGoogle ScholarCrossref
33.
Jenner  JL, Ordovas  JM, Lamon-Fava  S,  et al.  Effects of age, sex, and menopausal status on plasma lipoprotein(a) levels: the Framingham Offspring Study.   Circulation. 1993;87(4):1135-1141. doi:10.1161/01.CIR.87.4.1135PubMedGoogle ScholarCrossref
34.
Lanktree  MB, Anand  SS, Yusuf  S, Hegele  RA; SHARE Investigators.  Comprehensive analysis of genomic variation in the LPA locus and its relationship to plasma lipoprotein(a) in South Asians, Chinese, and European Caucasians.   Circ Cardiovasc Genet. 2010;3(1):39-46. doi:10.1161/CIRCGENETICS.109.907642PubMedGoogle ScholarCrossref
35.
Virani  SS, Brautbar  A, Davis  BC,  et al.  Associations between lipoprotein(a) levels and cardiovascular outcomes in black and white subjects: the Atherosclerosis Risk in Communities (ARIC) Study.   Circulation. 2012;125(2):241-249. doi:10.1161/CIRCULATIONAHA.111.045120PubMedGoogle ScholarCrossref
36.
Noureen  A, Fresser  F, Utermann  G, Schmidt  K.  Sequence variation within the KIV-2 copy number polymorphism of the human LPA gene in African, Asian, and European populations.   PLoS One. 2015;10(3):e0121582. doi:10.1371/journal.pone.0121582PubMedGoogle Scholar
37.
Khalifa  M, Noureen  A, Ertelthalner  K,  et al.  Lack of association of rs3798220 with small apolipoprotein(a) isoforms and high lipoprotein(a) levels in East and Southeast Asians.   Atherosclerosis. 2015;242(2):521-528. doi:10.1016/j.atherosclerosis.2015.07.015PubMedGoogle ScholarCrossref
38.
Paré  G, Çaku  A, McQueen  M,  et al; INTERHEART Investigators.  Lipoprotein(a) levels and the risk of myocardial infarction among 7 ethnic groups.   Circulation. 2019;139(12):1472-1482. doi:10.1161/CIRCULATIONAHA.118.034311PubMedGoogle ScholarCrossref
39.
Gupta  R, Vasisht  S, Bahl  VK, Wasir  HS.  Correlation of lipoprotein (a) to angiographically defined coronary artery disease in Indians.   Int J Cardiol. 1996;57(3):265-270. doi:10.1016/S0167-5273(96)02800-8PubMedGoogle ScholarCrossref
40.
Gambhir  JK, Kaur  H, Prabhu  KM, Morrisett  JD, Gambhir  DS.  Association between lipoprotein(a) levels, apo(a) isoforms and family history of premature CAD in young Asian Indians.   Clin Biochem. 2008;41(7-8):453-458. doi:10.1016/j.clinbiochem.2008.01.016PubMedGoogle ScholarCrossref
41.
Verbeek  R, Sandhu  MS, Hovingh  GK,  et al.  Lipoprotein(a) improves cardiovascular risk prediction based on established risk algorithms.   J Am Coll Cardiol. 2017;69(11):1513-1515. doi:10.1016/j.jacc.2017.01.017PubMedGoogle ScholarCrossref
42.
Di Angelantonio  E, Gao  P, Pennells  L,  et al; Emerging Risk Factors Collaboration.  Lipid-related markers and cardiovascular disease prediction.   JAMA. 2012;307(23):2499-2506.PubMedGoogle Scholar
43.
Mach  F, Baigent  C, Catapano  AL,  et al; ESC Scientific Document Group.  2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk.   Eur Heart J. 2020;41(1):111-188. doi:10.1093/eurheartj/ehz455PubMedGoogle ScholarCrossref
44.
Lloyd-Jones  DM.  Cardiovascular risk prediction: basic concepts, current status, and future directions.   Circulation. 2010;121(15):1768-1777. doi:10.1161/CIRCULATIONAHA.109.849166PubMedGoogle ScholarCrossref
45.
Suk Danik  J, Rifai  N, Buring  JE, Ridker  PM.  Lipoprotein(a), measured with an assay independent of apolipoprotein(a) isoform size, and risk of future cardiovascular events among initially healthy women.   JAMA. 2006;296(11):1363-1370. doi:10.1001/jama.296.11.1363PubMedGoogle ScholarCrossref
46.
Saleheen  D, Haycock  PC, Zhao  W,  et al.  Apolipoprotein(a) isoform size, lipoprotein(a) concentration, and coronary artery disease: a mendelian randomisation analysis.   Lancet Diabetes Endocrinol. 2017;5(7):524-533. doi:10.1016/S2213-8587(17)30088-8PubMedGoogle ScholarCrossref
47.
Langsted  A, Kamstrup  PR, Benn  M, Tybjærg-Hansen  A, Nordestgaard  BG.  High lipoprotein(a) as a possible cause of clinical familial hypercholesterolaemia: a prospective cohort study.   Lancet Diabetes Endocrinol. 2016;4(7):577-587. doi:10.1016/S2213-8587(16)30042-0PubMedGoogle ScholarCrossref
48.
Trinder  M, DeCastro  ML, Azizi  H,  et al.  Ascertainment bias in the association between elevated lipoprotein(a) and familial hypercholesterolemia.   J Am Coll Cardiol. 2020;75(21):2682-2693. doi:10.1016/j.jacc.2020.03.065PubMedGoogle ScholarCrossref
49.
Natarajan  P, Peloso  GM, Zekavat  SM,  et al; NHLBI TOPMed Lipids Working Group.  Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.   Nat Commun. 2018;9(1):3391. doi:10.1038/s41467-018-05747-8PubMedGoogle ScholarCrossref
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