Lipoprotein(a) and the risk of cardiovascular disease in the European population: results from the BiomarCaRE consortium
As promising compounds to lower Lipoprotein(a) (Lp(a)) are emerging, the need for a precise characterization and comparability of the Lp(a)-associated cardiovascular risk is increasing. Therefore, we aimed to evaluate the distribution of Lp(a) concentrations across the European population, to charac...
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| Veröffentlicht in: | European heart journal Jg. 38; H. 32; S. 2490 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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England
21.08.2017
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| ISSN: | 1522-9645, 1522-9645 |
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| Abstract | As promising compounds to lower Lipoprotein(a) (Lp(a)) are emerging, the need for a precise characterization and comparability of the Lp(a)-associated cardiovascular risk is increasing. Therefore, we aimed to evaluate the distribution of Lp(a) concentrations across the European population, to characterize the association with cardiovascular outcomes and to provide high comparability of the Lp(a)-associated cardiovascular risk by use of centrally determined Lp(a) concentrations.
Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE)-project, we analysed data of 56 804 participants from 7 prospective population-based cohorts across Europe with a maximum follow-up of 24 years. All Lp(a) measurements were performed in the central BiomarCaRE laboratory (Biokit Quantia Lp(a)-Test; Abbott Diagnostics). The three endpoints considered were incident major coronary events (MCE), incident cardiovascular disease (CVD) events, and total mortality. We found lower Lp(a) levels in Northern European cohorts (median 4.9 mg/dL) compared to central (median 7.9 mg/dL) and Southern European cohorts (10.9 mg/dL) (Jonckheere-Terpstra test P < 0.001). Kaplan-Meier curves showed the highest event rate of MCE and CVD events for Lp(a) levels ≥90th percentile (log-rank test: P < 0.001 for MCE and CVD). Cox regression models adjusted for age, sex, and cardiovascular risk factors revealed a significant association of Lp(a) levels with MCE and CVD with a hazard ratio (HR) of 1.30 for MCE [95% confidence interval (CI) 1.15‒1.46] and of 1.25 for CVD (95% CI 1.12‒1.39) for Lp(a) levels in the 67‒89th percentile and a HR of 1.49 for MCE (95% CI 1.29‒1.73) and of 1.44 for CVD (95% CI 1.25‒1.65) for Lp(a) levels ≥ 90th percentile vs. Lp(a) levels in the lowest third (P < 0.001 for all). There was no significant association between Lp(a) levels and total mortality. Subgroup analysis for a continuous version of cube root transformed Lp(a) identified the highest Lp(a)-associated risk in individuals with diabetes [HR for MCE 1.31 (95% CI 1.15‒1.50)] and for CVD 1.22 (95% CI 1.08‒1.38) compared to those without diabetes [HR for MCE 1.15 (95% CI 1.08‒1.21; HR for CVD 1.13 (1.07-1.19)] while no difference of the Lp(a)- associated risk were seen for other cardiovascular high risk states. The addition of Lp(a) levels to a prognostic model for MCE and CVD revealed only a marginal but significant C-index discrimination measure increase (0.001 for MCE and CVD; P < 0.05) and net reclassification improvement (0.010 for MCE and 0.011 for CVD).
In this large dataset on harmonized Lp(a) determination, we observed regional differences within the European population. Elevated Lp(a) was robustly associated with an increased risk for MCE and CVD in particular among individuals with diabetes. These results may lead to better identification of target populations who might benefit from future Lp(a)-lowering therapies. |
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| AbstractList | As promising compounds to lower Lipoprotein(a) (Lp(a)) are emerging, the need for a precise characterization and comparability of the Lp(a)-associated cardiovascular risk is increasing. Therefore, we aimed to evaluate the distribution of Lp(a) concentrations across the European population, to characterize the association with cardiovascular outcomes and to provide high comparability of the Lp(a)-associated cardiovascular risk by use of centrally determined Lp(a) concentrations.AIMSAs promising compounds to lower Lipoprotein(a) (Lp(a)) are emerging, the need for a precise characterization and comparability of the Lp(a)-associated cardiovascular risk is increasing. Therefore, we aimed to evaluate the distribution of Lp(a) concentrations across the European population, to characterize the association with cardiovascular outcomes and to provide high comparability of the Lp(a)-associated cardiovascular risk by use of centrally determined Lp(a) concentrations.Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE)-project, we analysed data of 56 804 participants from 7 prospective population-based cohorts across Europe with a maximum follow-up of 24 years. All Lp(a) measurements were performed in the central BiomarCaRE laboratory (Biokit Quantia Lp(a)-Test; Abbott Diagnostics). The three endpoints considered were incident major coronary events (MCE), incident cardiovascular disease (CVD) events, and total mortality. We found lower Lp(a) levels in Northern European cohorts (median 4.9 mg/dL) compared to central (median 7.9 mg/dL) and Southern European cohorts (10.9 mg/dL) (Jonckheere-Terpstra test P < 0.001). Kaplan-Meier curves showed the highest event rate of MCE and CVD events for Lp(a) levels ≥90th percentile (log-rank test: P < 0.001 for MCE and CVD). Cox regression models adjusted for age, sex, and cardiovascular risk factors revealed a significant association of Lp(a) levels with MCE and CVD with a hazard ratio (HR) of 1.30 for MCE [95% confidence interval (CI) 1.15‒1.46] and of 1.25 for CVD (95% CI 1.12‒1.39) for Lp(a) levels in the 67‒89th percentile and a HR of 1.49 for MCE (95% CI 1.29‒1.73) and of 1.44 for CVD (95% CI 1.25‒1.65) for Lp(a) levels ≥ 90th percentile vs. Lp(a) levels in the lowest third (P < 0.001 for all). There was no significant association between Lp(a) levels and total mortality. Subgroup analysis for a continuous version of cube root transformed Lp(a) identified the highest Lp(a)-associated risk in individuals with diabetes [HR for MCE 1.31 (95% CI 1.15‒1.50)] and for CVD 1.22 (95% CI 1.08‒1.38) compared to those without diabetes [HR for MCE 1.15 (95% CI 1.08‒1.21; HR for CVD 1.13 (1.07-1.19)] while no difference of the Lp(a)- associated risk were seen for other cardiovascular high risk states. The addition of Lp(a) levels to a prognostic model for MCE and CVD revealed only a marginal but significant C-index discrimination measure increase (0.001 for MCE and CVD; P < 0.05) and net reclassification improvement (0.010 for MCE and 0.011 for CVD).METHODS AND RESULTSBased on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE)-project, we analysed data of 56 804 participants from 7 prospective population-based cohorts across Europe with a maximum follow-up of 24 years. All Lp(a) measurements were performed in the central BiomarCaRE laboratory (Biokit Quantia Lp(a)-Test; Abbott Diagnostics). The three endpoints considered were incident major coronary events (MCE), incident cardiovascular disease (CVD) events, and total mortality. We found lower Lp(a) levels in Northern European cohorts (median 4.9 mg/dL) compared to central (median 7.9 mg/dL) and Southern European cohorts (10.9 mg/dL) (Jonckheere-Terpstra test P < 0.001). Kaplan-Meier curves showed the highest event rate of MCE and CVD events for Lp(a) levels ≥90th percentile (log-rank test: P < 0.001 for MCE and CVD). Cox regression models adjusted for age, sex, and cardiovascular risk factors revealed a significant association of Lp(a) levels with MCE and CVD with a hazard ratio (HR) of 1.30 for MCE [95% confidence interval (CI) 1.15‒1.46] and of 1.25 for CVD (95% CI 1.12‒1.39) for Lp(a) levels in the 67‒89th percentile and a HR of 1.49 for MCE (95% CI 1.29‒1.73) and of 1.44 for CVD (95% CI 1.25‒1.65) for Lp(a) levels ≥ 90th percentile vs. Lp(a) levels in the lowest third (P < 0.001 for all). There was no significant association between Lp(a) levels and total mortality. Subgroup analysis for a continuous version of cube root transformed Lp(a) identified the highest Lp(a)-associated risk in individuals with diabetes [HR for MCE 1.31 (95% CI 1.15‒1.50)] and for CVD 1.22 (95% CI 1.08‒1.38) compared to those without diabetes [HR for MCE 1.15 (95% CI 1.08‒1.21; HR for CVD 1.13 (1.07-1.19)] while no difference of the Lp(a)- associated risk were seen for other cardiovascular high risk states. The addition of Lp(a) levels to a prognostic model for MCE and CVD revealed only a marginal but significant C-index discrimination measure increase (0.001 for MCE and CVD; P < 0.05) and net reclassification improvement (0.010 for MCE and 0.011 for CVD).In this large dataset on harmonized Lp(a) determination, we observed regional differences within the European population. Elevated Lp(a) was robustly associated with an increased risk for MCE and CVD in particular among individuals with diabetes. These results may lead to better identification of target populations who might benefit from future Lp(a)-lowering therapies.CONCLUSIONIn this large dataset on harmonized Lp(a) determination, we observed regional differences within the European population. Elevated Lp(a) was robustly associated with an increased risk for MCE and CVD in particular among individuals with diabetes. These results may lead to better identification of target populations who might benefit from future Lp(a)-lowering therapies. As promising compounds to lower Lipoprotein(a) (Lp(a)) are emerging, the need for a precise characterization and comparability of the Lp(a)-associated cardiovascular risk is increasing. Therefore, we aimed to evaluate the distribution of Lp(a) concentrations across the European population, to characterize the association with cardiovascular outcomes and to provide high comparability of the Lp(a)-associated cardiovascular risk by use of centrally determined Lp(a) concentrations. Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE)-project, we analysed data of 56 804 participants from 7 prospective population-based cohorts across Europe with a maximum follow-up of 24 years. All Lp(a) measurements were performed in the central BiomarCaRE laboratory (Biokit Quantia Lp(a)-Test; Abbott Diagnostics). The three endpoints considered were incident major coronary events (MCE), incident cardiovascular disease (CVD) events, and total mortality. We found lower Lp(a) levels in Northern European cohorts (median 4.9 mg/dL) compared to central (median 7.9 mg/dL) and Southern European cohorts (10.9 mg/dL) (Jonckheere-Terpstra test P < 0.001). Kaplan-Meier curves showed the highest event rate of MCE and CVD events for Lp(a) levels ≥90th percentile (log-rank test: P < 0.001 for MCE and CVD). Cox regression models adjusted for age, sex, and cardiovascular risk factors revealed a significant association of Lp(a) levels with MCE and CVD with a hazard ratio (HR) of 1.30 for MCE [95% confidence interval (CI) 1.15‒1.46] and of 1.25 for CVD (95% CI 1.12‒1.39) for Lp(a) levels in the 67‒89th percentile and a HR of 1.49 for MCE (95% CI 1.29‒1.73) and of 1.44 for CVD (95% CI 1.25‒1.65) for Lp(a) levels ≥ 90th percentile vs. Lp(a) levels in the lowest third (P < 0.001 for all). There was no significant association between Lp(a) levels and total mortality. Subgroup analysis for a continuous version of cube root transformed Lp(a) identified the highest Lp(a)-associated risk in individuals with diabetes [HR for MCE 1.31 (95% CI 1.15‒1.50)] and for CVD 1.22 (95% CI 1.08‒1.38) compared to those without diabetes [HR for MCE 1.15 (95% CI 1.08‒1.21; HR for CVD 1.13 (1.07-1.19)] while no difference of the Lp(a)- associated risk were seen for other cardiovascular high risk states. The addition of Lp(a) levels to a prognostic model for MCE and CVD revealed only a marginal but significant C-index discrimination measure increase (0.001 for MCE and CVD; P < 0.05) and net reclassification improvement (0.010 for MCE and 0.011 for CVD). In this large dataset on harmonized Lp(a) determination, we observed regional differences within the European population. Elevated Lp(a) was robustly associated with an increased risk for MCE and CVD in particular among individuals with diabetes. These results may lead to better identification of target populations who might benefit from future Lp(a)-lowering therapies. |
| Author | Veronesi, Giovanni Jousilahti, Pekka Signorini, Stefano G Kontto, Jukka Brambilla, Paolo Ojeda, Francisco Niiranen, Teemu Zeller, Tanja Linneberg, Allan Giampaoli, Simona Jørgensen, Torben Makarova, Nataliya Salomaa, Veikko Landmesser, Ulf Schnabel, Renate B Brunner, Fabian J Kee, Frank Costanzo, Simona Iacoviello, Licia Koenig, Wolfgang Thorand, Barbara Ferrario, Marco M Waldeyer, Christoph Meisinger, Christa Blankenberg, Stefan Kuulasmaa, Kari Palmieri, Luigi Yarnell, John |
| Author_xml | – sequence: 1 givenname: Christoph surname: Waldeyer fullname: Waldeyer, Christoph organization: Department for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany – sequence: 2 givenname: Nataliya surname: Makarova fullname: Makarova, Nataliya organization: German Center for Cardiovascular Research (DZHK e.V.), partner site Hamburg/Lübeck/Kiel, Germany – sequence: 3 givenname: Tanja surname: Zeller fullname: Zeller, Tanja organization: German Center for Cardiovascular Research (DZHK e.V.), partner site Hamburg/Lübeck/Kiel, Germany – sequence: 4 givenname: Renate B surname: Schnabel fullname: Schnabel, Renate B organization: German Center for Cardiovascular Research (DZHK e.V.), partner site Hamburg/Lübeck/Kiel, Germany – sequence: 5 givenname: Fabian J surname: Brunner fullname: Brunner, Fabian J organization: Department for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany – sequence: 6 givenname: Torben surname: Jørgensen fullname: Jørgensen, Torben organization: Medical Faculty, Aalborg University, Aalborg, Denmark – sequence: 7 givenname: Allan surname: Linneberg fullname: Linneberg, Allan organization: Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark – sequence: 8 givenname: Teemu surname: Niiranen fullname: Niiranen, Teemu organization: National Institute for Health and Welfare, Helsinki, Finland – sequence: 9 givenname: Veikko surname: Salomaa fullname: Salomaa, Veikko organization: National Institute for Health and Welfare, Helsinki, Finland – sequence: 10 givenname: Pekka surname: Jousilahti fullname: Jousilahti, Pekka organization: National Institute for Health and Welfare, Helsinki, Finland – sequence: 11 givenname: John surname: Yarnell fullname: Yarnell, John organization: Centre for Public Health, Queens University of Belfast, Belfast, Northern Ireland – sequence: 12 givenname: Marco M surname: Ferrario fullname: Ferrario, Marco M organization: Department of Medicine and Surgery, Research Centre in Epidemiology and Preventive Medicine, University of Insubria, Varese, Italy – sequence: 13 givenname: Giovanni surname: Veronesi fullname: Veronesi, Giovanni organization: Department of Medicine and Surgery, Research Centre in Epidemiology and Preventive Medicine, University of Insubria, Varese, Italy – sequence: 14 givenname: Paolo surname: Brambilla fullname: Brambilla, Paolo organization: Department of Medicina e Chirurgia, Università degli studi di Milano-Bicocca, Italy – sequence: 15 givenname: Stefano G surname: Signorini fullname: Signorini, Stefano G organization: Department of Medicina e Chirurgia, Università degli studi di Milano-Bicocca, Italy – sequence: 16 givenname: Licia surname: Iacoviello fullname: Iacoviello, Licia organization: Department of Epidemiology and Prevention, Laboratory of Molecular and Nutritional Epidemiology, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy – sequence: 17 givenname: Simona surname: Costanzo fullname: Costanzo, Simona organization: Department of Epidemiology and Prevention, Laboratory of Molecular and Nutritional Epidemiology, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy – sequence: 18 givenname: Simona surname: Giampaoli fullname: Giampaoli, Simona organization: Istituto Superiore di Sanità, Rome, Italy – sequence: 19 givenname: Luigi surname: Palmieri fullname: Palmieri, Luigi organization: Istituto Superiore di Sanità, Rome, Italy – sequence: 20 givenname: Christa surname: Meisinger fullname: Meisinger, Christa organization: Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany – sequence: 21 givenname: Barbara surname: Thorand fullname: Thorand, Barbara organization: Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany – sequence: 22 givenname: Frank surname: Kee fullname: Kee, Frank organization: Centre for Public Health, Queens University of Belfast, Belfast, Northern Ireland – sequence: 23 givenname: Wolfgang surname: Koenig fullname: Koenig, Wolfgang organization: German Center for Cardiovascular Research (DZHK e.V.), partner site Munich Heart Alliance, Munich, Germany – sequence: 24 givenname: Francisco surname: Ojeda fullname: Ojeda, Francisco organization: Department for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany – sequence: 25 givenname: Jukka surname: Kontto fullname: Kontto, Jukka organization: National Institute for Health and Welfare, Helsinki, Finland – sequence: 26 givenname: Ulf surname: Landmesser fullname: Landmesser, Ulf organization: German Center for Cardiovascular Research (DZHK e.V.), partner site Berlin, Berlin, Germany – sequence: 27 givenname: Kari surname: Kuulasmaa fullname: Kuulasmaa, Kari organization: National Institute for Health and Welfare, Helsinki, Finland – sequence: 28 givenname: Stefan surname: Blankenberg fullname: Blankenberg, Stefan organization: German Center for Cardiovascular Research (DZHK e.V.), partner site Hamburg/Lübeck/Kiel, Germany |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28449027$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | The Author 2017. Published on behalf of the European Society of Cardiology. |
| Copyright_xml | – notice: The Author 2017. Published on behalf of the European Society of Cardiology. |
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| Keywords | BiomarCaRE (Biomarker for Cardiovascular Risk Assessment in Europe) Lipoprotein(a) MORGAM (MONICA Risk Genetics Archiving and Monograph) Mortality Cardiovascular risk |
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| Title | Lipoprotein(a) and the risk of cardiovascular disease in the European population: results from the BiomarCaRE consortium |
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