Association of Circulating Monocyte Chemoattractant Protein–1 Levels With Cardiovascular Mortality: A Meta-analysis of Population-Based Studies | Cardiology | JAMA Cardiology | JAMA Network
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Figure.  Associations Between Baseline Circulating Monocyte-Chemoattractant Protein–1 Levels and Risk of Coronary Heart Disease, Nonfatal Myocardial Infarction, and Cardiovascular Death
Associations Between Baseline Circulating Monocyte-Chemoattractant Protein–1 Levels and Risk of Coronary Heart Disease, Nonfatal Myocardial Infarction, and Cardiovascular Death

Shown are the results from random-effects meta-analyses of the pooled sample consisting of 7 population-based studies, as derived from model 1 (adjusted for age, sex, and race/ethnicity) (A) and model 2 (adjusted for age, sex, race/ethnicity, and vascular risk factors) (B). The vascular risk factors adjusted for in model 2 include hypertension, low-density lipoprotein cholesterol levels, use of statins, diabetes mellitus, body mass index (per 1–kg/m2 increment), smoking (current vs noncurrent), estimated glomerular filtration rate (per 1–mL/min/1.73 m2 increment), physical activity, and alcohol consumption at baseline. Analyses for 1-SD increment correspond to natural log–transformed MCP-1 levels. The Monitoring of Trends and Determinants in Cardiovascular Disease–Kooperative Gesundheitsforschung in der Region Augsburg (MONICA/KORA) study is not included in any of the analyses for nonfatal myocardial infarction and cardiovascular death.

Table.  Descriptive Baseline Characteristics of the 7 Included Population-Based Cohort Studies
Descriptive Baseline Characteristics of the 7 Included Population-Based Cohort Studies
Supplement.

eMethods. Literature Search.

eTable 1. Summary of the study design, population characteristics, methods used for quantifying circulating MCP-1 levels, outcome definitions, and assessments in the cohorts included in the meta-analysis.

eTable 2. Quality characteristics of the included studies according to the Newcastle-Ottawa Scale.

eTable 3. Associations between baseline circulating MCP-1 levels and risk of incident coronary heart disease, incident non-fatal myocardial infarction, and cardiovascular death. Shown are the results from random-effects meta-analyses of the pooled sample consisting of six population-based studies.

eTable 4. Associations between baseline circulating MCP-1 levels and risk of incident coronary heart disease, incident non-fatal myocardial infarction, and cardiovascular death in sensitivity analyses excluding events that occurred in the first 5 years after follow-up. Shown are the results from random-effects meta-analyses of the pooled sample consisting of six population-based studies.

eTable 5. C-statistics of a model adjusted for age, sex, and ethnicity (Model 1), as well as of a model additionally adjusted for vascular risk factors (Model 2) for predicting incident coronary heart disease, incident non-fatal myocardial infarction, and cardiovascular death before and after inclusion of MCP-1 levels. Shown are the results from the pooled meta-analyses across six population-based studies.

eFigure 1. Study-specific and pooled hazard ratios for incident coronary heart disease per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, and race (Model 1).

eFigure 2. Study-specific and pooled hazard ratios for incident non-fatal myocardial infarction per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, and race (Model 1).

eFigure 3. Study-specific and pooled hazard ratios for cardiovascular death per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, and race (Model 1).

eFigure 4. Study-specific and pooled hazard ratios for incident coronary heart disease per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, race, and vascular risk factors (Model 2).

eFigure 5. Study-specific and pooled hazard ratios for incident non-fatal myocardial infarction per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, race, and vascular risk factors (Model 2).

eFigure 6. Study-specific and pooled hazard ratios for cardiovascular death per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, race, and vascular risk factors (Model 2).

eFigure 7. Study-specific and pooled hazard ratios for non-cardiovascular death per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, and race (Model 1).

eFigure 8. Study-specific and pooled hazard ratios for non-cardiovascular death per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles after adjusting for age, sex, race, and vascular risk factors (Model 2).

eFigure 9. Pooled hazard ratios for incident coronary heart disease per standard deviation increase in ln-transformed circulating MCP-1 levels, as derived from random-effects meta-analyses stratified by pre-defined study variables.

eFigure 10. Pooled hazard ratios for incident non-fatal myocardial infarction per standard deviation increase in ln-transformed circulating MCP-1 levels, as derived from random-effects meta-analyses stratified by pre-defined study variables.

eFigure 11. Pooled hazard ratios for cardiovascular death per standard deviation increase in ln-transformed circulating MCP-1 levels, as derived from random-effects meta-analyses stratified by pre-defined study variables.

eFigure 12. Pooled hazard ratios for (A) incident coronary heart disease CAD), (B) non-fatal myocardial infarction (NFMI), and (C) cardiovascular death (CVD) per standard deviation increase in ln-transformed circulating MCP-1 levels and across MCP-1 level quartiles in consecutive models adjusting for age, sex, race, vascular risk factors, high-sensitivity C-reactive protein (CRP), as well as interleukin-6 (IL6) circulating levels.

eReferences.

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Ridker  PM, Everett  BM, Thuren  T,  et al; CANTOS Trial Group.  Antiinflammatory therapy with canakinumab for atherosclerotic disease.   N Engl J Med. 2017;377(12):1119-1131. doi:10.1056/NEJMoa1707914PubMedGoogle ScholarCrossref
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Tardif  JC, Kouz  S, Waters  DD,  et al.  Efficacy and safety of low-dose colchicine after myocardial infarction.   N Engl J Med. 2019;381(26):2497-2505. doi:10.1056/NEJMoa1912388PubMedGoogle ScholarCrossref
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Ridker  PM, Everett  BM, Pradhan  A,  et al; CIRT Investigators.  Low-dose methotrexate for the prevention of atherosclerotic events.   N Engl J Med. 2019;380(8):752-762. doi:10.1056/NEJMoa1809798PubMedGoogle ScholarCrossref
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Ridker  PM.  From C-reactive protein to interleukin-6 to interleukin-1: moving upstream to identify novel targets for atheroprotection.   Circ Res. 2016;118(1):145-156. doi:10.1161/CIRCRESAHA.115.306656PubMedGoogle ScholarCrossref
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Aday  AW, Ridker  PM.  Targeting residual inflammatory risk: a shifting paradigm for atherosclerotic disease.   Front Cardiovasc Med. 2019;6:16. doi:10.3389/fcvm.2019.00016PubMedGoogle ScholarCrossref
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Georgakis  MK, Gill  D, Rannikmäe  K,  et al.  Genetically determined levels of circulating cytokines and risk of stroke.   Circulation. 2019;139(2):256-268. doi:10.1161/CIRCULATIONAHA.118.035905PubMedGoogle ScholarCrossref
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Bot  I, Ortiz Zacarías  NV, de Witte  WE,  et al.  A novel CCR2 antagonist inhibits atherogenesis in apoE deficient mice by achieving high receptor occupancy.   Sci Rep. 2017;7(1):52. doi:10.1038/s41598-017-00104-zPubMedGoogle ScholarCrossref
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Inoue  S, Egashira  K, Ni  W,  et al.  Anti-monocyte chemoattractant protein-1 gene therapy limits progression and destabilization of established atherosclerosis in apolipoprotein E-knockout mice.   Circulation. 2002;106(21):2700-2706. doi:10.1161/01.CIR.0000038140.80105.ADPubMedGoogle ScholarCrossref
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Georgakis  MK, Malik  R, Björkbacka  H,  et al.  Circulating monocyte chemoattractant protein-1 and risk of stroke: meta-analysis of population-based studies involving 17 180 individuals.   Circ Res. 2019;125(8):773-782. doi:10.1161/CIRCRESAHA.119.315380PubMedGoogle ScholarCrossref
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Wells  GA, Shea  B, O’Connell  D, Peterson  J, Welch  V, Losos  M. The Newcastle-Ottawa Scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses. Published 2014. Accessed June 7, 2018. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
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de Lemos  JA, Morrow  DA, Sabatine  MS,  et al.  Association between plasma levels of monocyte chemoattractant protein-1 and long-term clinical outcomes in patients with acute coronary syndromes.   Circulation. 2003;107(5):690-695. doi:10.1161/01.CIR.0000049742.68848.99PubMedGoogle ScholarCrossref
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de Lemos  JA, Morrow  DA, Blazing  MA,  et al.  Serial measurement of monocyte chemoattractant protein-1 after acute coronary syndromes: results from the A to Z trial.   J Am Coll Cardiol. 2007;50(22):2117-2124. doi:10.1016/j.jacc.2007.06.057PubMedGoogle ScholarCrossref
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Gu  L, Okada  Y, Clinton  SK,  et al.  Absence of monocyte chemoattractant protein-1 reduces atherosclerosis in low density lipoprotein receptor-deficient mice.   Mol Cell. 1998;2(2):275-281. doi:10.1016/S1097-2765(00)80139-2PubMedGoogle ScholarCrossref
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Boring  L, Gosling  J, Cleary  M, Charo  IF.  Decreased lesion formation in CCR2-/- mice reveals a role for chemokines in the initiation of atherosclerosis.   Nature. 1998;394(6696):894-897. doi:10.1038/29788PubMedGoogle ScholarCrossref
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Dewald  O, Zymek  P, Winkelmann  K,  et al.  CCL2/monocyte chemoattractant protein-1 regulates inflammatory responses critical to healing myocardial infarcts.   Circ Res. 2005;96(8):881-889. doi:10.1161/01.RES.0000163017.13772.3aPubMedGoogle ScholarCrossref
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Nielsen  MA, Lomholt  S, Mellemkjaer  A, Andersen  MN, Buckley  CD, Kragstrup  TW.  Responses to cytokine inhibitors associated with cellular composition in models of immune-mediated inflammatory arthritis.   ACR Open Rheumatol. 2020;2(1):3-10. doi:10.1002/acr2.11094PubMedGoogle ScholarCrossref
Brief Report
November 4, 2020

Association of Circulating Monocyte Chemoattractant Protein–1 Levels With Cardiovascular Mortality: A Meta-analysis of Population-Based Studies

Author Affiliations
  • 1Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-University, Munich, Germany
  • 2Graduate School for Systemic Neurosciences, Ludwig-Maximilians-University, Munich, Germany
  • 3Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
  • 4Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
  • 5Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
  • 6Institute of Applied Health Sciences, School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
  • 7Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
  • 8German Center for Diabetes Research, München-Neuherberg, Germany
  • 9Department of Medicine, Baylor College of Medicine, Houston, Texas
  • 10Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
  • 11Amsterdam UMC, University of Amsterdam, Department of Cardiology, Amsterdam, the Netherlands
  • 12Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
  • 13German Research Center for Cardiovascular Disease, Partner Site of Munich Heart Alliance, Munich, Germany
  • 14Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
  • 15Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
  • 16Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
  • 17Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
  • 18Institute of Medical Information Sciences, Biometry and Epidemiology, Ludwig-Maximilians-University, Munich, Germany
  • 19Section of Cardiovascular Medicine and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
  • 20Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
  • 21Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University, Framingham, Massachusetts
  • 22Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
  • 23German Centre for Neurodegenerative Diseases, Munich, Germany
JAMA Cardiol. 2021;6(5):587-592. doi:10.1001/jamacardio.2020.5392
Key Points

Question  Are circulating monocyte-chemoattractant protein–1 (MCP-1) levels associated with the risk of cardiovascular disease in the general population?

Findings  In this meta-analysis of 7 population-based studies involving 21 401 individuals who were free of overt cardiovascular disease, higher baseline circulating MCP-1 levels were associated with higher risk of cardiovascular mortality over a follow-up extending beyond 20 years.

Meaning  By complementing evidence from previous genetic and experimental studies, these results provide additional support for a key role of MCP-1 in cardiovascular disease development.

Abstract

Importance  Human genetics and studies in experimental models support a key role of monocyte-chemoattractant protein–1 (MCP-1) in atherosclerosis. Yet, the associations of circulating MCP-1 levels with risk of coronary heart disease and cardiovascular death in the general population remain largely unexplored.

Objective  To explore whether circulating levels of MCP-1 are associated with risk of incident coronary heart disease, myocardial infarction, and cardiovascular mortality in the general population.

Data Sources and Selection  Population-based cohort studies, identified through a systematic review, that have examined associations of circulating MCP-1 levels with cardiovascular end points.

Data Extraction and Synthesis  Using a prespecified harmonized analysis plan, study-specific summary data were obtained from Cox regression models after excluding individuals with overt cardiovascular disease at baseline. Derived hazard ratios (HRs) were synthesized using random-effects meta-analyses.

Main Outcomes and Measures  Incident coronary heart disease (myocardial infarction, coronary revascularization, and unstable angina), nonfatal myocardial infarction, and cardiovascular death (from cardiac or cerebrovascular causes).

Results  The meta-analysis included 7 cohort studies involving 21 401 individuals (mean [SD] age, 53.7 [10.2] years; 10 012 men [46.8%]). Mean (SD) follow-up was 15.3 (4.5) years (326 392 person-years at risk). In models adjusting for age, sex, and race/ethnicity, higher MCP-1 levels at baseline were associated with increased risk of coronary heart disease (HR per 1-SD increment in MCP-1 levels: 1.06 [95% CI, 1.01-1.11]; P = .01), nonfatal myocardial infarction (HR, 1.07 [95% CI, 1.01-1.13]; P = .02), and cardiovascular death (HR, 1.12 [95% CI, 1.05-1.20]; P < .001). In analyses comparing MCP-1 quartiles, these associations followed dose-response patterns. After additionally adjusting for vascular risk factors, the risk estimates were attenuated, but the associations of MCP-1 levels with cardiovascular death remained statistically significant, as did the association of MCP-1 levels in the upper quartile with coronary heart disease. There was no significant heterogeneity; the results did not change in sensitivity analyses excluding events occurring in the first 5 years after MCP-1 measurement, and the risk estimates were stable after additional adjustments for circulating levels of interleukin-6 and high-sensitivity C-reactive protein.

Conclusions and Relevance  Higher circulating MCP-1 levels are associated with higher long-term cardiovascular mortality in community-dwelling individuals free of overt cardiovascular disease. These findings provide further support for a key role of MCP-1-signaling in cardiovascular disease.

Introduction

The results of the recent Canakinumab Antiinflammatory Thrombosis Outcome Study (CANTOS) trial, Cardiovascular Inflammation Reduction Trial (CIRT), and Colchicine Cardiovascular Outcomes Trial (COLCOT)1-3 emphasize the promise of targeting specific inflammatory pathways for lowering cardiovascular risk. While recent studies have focused on the interleukin-1β (IL-1β)–interleukin-6 (IL-6)–C-reactive protein (CRP) axis,4 a range of proinflammatory cytokines have been implicated in atherosclerosis.5 In a recent mendelian randomization study examining multiple cytokines, we found genetically predicted levels of monocyte-chemoattractant-protein–1 (MCP-1) to be associated with higher risk of coronary heart disease (CHD) and ischemic stroke.6 The presence of MCP-1 recruits monocytes to the arterial wall, and experimental studies of atherosclerosis suggest that targeting MCP-1 signaling attenuates atherosclerosis progression and plaque destabilization.7,8 Circulating MCP-1 levels have been associated with increased long-term risk of incident stroke,9 but associations with other cardiovascular end points in the general population remain largely unexplored. We leveraged data from 7 population-based cohorts encompassing 21 401 individuals without overt cardiovascular disease and investigated associations of baseline circulating MCP-1 with incident CHD, nonfatal myocardial infarction, and cardiovascular death over a follow-up period extending beyond 20 years.

Methods

Studies included in this meta-analysis were identified through systematic review, as previously described (eMethods in the Supplement).9 Specifically, PubMed was searched for population-based cohort studies examining associations between MCP-1 levels and incident vascular outcomes up to July 2019. The corresponding authors of identified studies were contacted and agreed on a harmonized analysis plan. Contributing studies are described in eTable 1 in the Supplement. Baseline data were collected from 1984 to 2002, with the range of data collection dates varying between studies. Outcomes of interest included incident CHD (a composite of fatal and nonfatal myocardial infarction, unstable angina, and coronary revascularization), nonfatal myocardial infarction (no death within 28 days after an event), and cardiovascular mortality (death from any cardiac or cerebrovascular cause). Individuals with a baseline history of CHD, heart failure, stroke, or peripheral artery disease were excluded from the analyses. Study quality was assessed with the Newcastle-Ottawa scale.10 Studies fulfilled all quality criteria (eTable 2 in the Supplement).

Cox regression models were fitted in each study. Natural log–transformed MCP-1 levels were incorporated in the models as continuous (in 1-SD increments) and also categorized in quartiles. Because of the different MCP-1 quantification assays, absolute MCP-1 values were not considered. Two main models were applied: model 1 was adjusted for age, sex, and race/ethnicity; model 2 was additionally adjusted for baseline vascular risk factors, including hypertension (documented diagnosis; systolic blood pressure, ≥140 mm Hg; diastolic blood pressure, ≥90 mm Hg; or antihypertensive medication use), low-density lipoprotein cholesterol levels, use of statins, diabetes (documented diagnosis; hemoglobin A1c, ≥6.5% [to convert to proportion of total hemoglobin, multiply by 0.01]; fasting glucose, ≥126 mg/dL [to convert to millimoles per liter, multiply by 0.0555]; random glucose, ≥200 mg/dL; or glucose-lowering medication use), body mass index (calculated as weight in kilograms divided by height in meters squared), smoking (current vs noncurrent), estimated glomerular filtration rate, physical activity, and alcohol consumption. In subsequent models, additional adjustments for circulating IL-6 and high-sensitivity CRP levels were applied. The hazard ratios (HRs) derived from each study were pooled with random-effects meta-analyses (preselected because of differences in MCP-1 assays). Heterogeneity was assessed with the I2 and Cochran Q statistics (I2 > 50% and P < .10 were considered significant). We further performed subgroup analyses by age (<50, 50-64, and ≥65 years), sex, hypertension status, diabetes status, and body mass index (<30 and ≥30). To minimize reverse-causation risk, sensitivity analyses were restricted to incident events occurring 5 or more years after MCP-1 measurements by censoring individuals with events at earlier points. Statistical significance was set at 2-sided P < .05. Meta-analyses were conducted with Stata version 13.0 (StataCorp). Statistical analysis was carried out from August 2019 to February 2020.

Results

Seven population-based cohort studies contributed data for this meta-analysis. A total of 21 401 individuals (mean [SD] age, 53.7 [10.2] years; 10 012 men [46.8%]; Table) without overt cardiovascular disease at baseline were followed for a mean (SD) interval of 15.3 (4.5) years (326 392 person-years at risk). A total of 3283 incident cases of CHD, 1221 cases of nonfatal myocardial infarction, and 1568 cardiovascular deaths were recorded during follow-up.

Higher baseline MCP-1 levels were associated with increased risk of CHD (HR per 1-SD increment, 1.06 [95% CI, 1.01-1.11]; P = .01), nonfatal myocardial infarction (HR, 1.07 [95% CI, 1.01-1.13]; P = .02), and cardiovascular death (HR, 1.12 [95% CI, 1.05-1.20]; P < .001) in models adjusted for age, sex, and race/ethnicity (Figure, A; eTable 3 in the Supplement). These associations showed stepwise increases across MCP-1 quartiles. After additionally adjusting for vascular risk factors, the association between MCP-1 levels and cardiovascular death remained significant (HR per 1-SD increment, 1.09 [95% CI, 1.03-1.16]; P = .004), as did the association between MCP-1 levels in the upper quartile with CHD (Figure, B). There was no evidence of significant heterogeneity (I2 < 50%, P > .10; eFigures 1-6 in the Supplement). The MCP-1 levels were also associated with noncardiovascular death, but the association was nonsignificant after additional adjustments for vascular risk factors (eFigures 7 and 8 in the Supplement).

In sensitivity analyses excluding events occurring in the first 5 years of follow-up, there were significant associations of MCP-1 levels with incident nonfatal myocardial infarction (HR per 1-SD increment, 1.08 [95% CI, 1.001-1.16]; P = .048) and cardiovascular death (HR per 1-SD increment, 1.10 [95% CI, 1.02-1.18]; P = .02) after adjusting for demographics and vascular risk factors (eTable 4 in the Supplement). In subgroup analyses stratifying for age, sex, hypertension, diabetes mellitus, and body mass index, there was no indication for between-subgroup heterogeneity, except for a stronger association with cardiovascular death in individuals without hypertension (HR, 1.17 [95% CI, 1.08-1.27]; P = .045; eFigures 9-11 in the Supplement). Additional adjustments for IL-6 and high-sensitivity CRP levels (subset of 5 studies; 16 621 individuals) did not substantially attenuate the risk estimates (eFigure 12 in the Supplement). When exploring the additive predictive value of MCP-1, we found no significant increment on top of vascular risk factors (C statistic for cardiovascular death with MCP-1, 0.779 vs without MCP-1, 0.774; eTable 5 in the Supplement).

Discussion

Among 21 401 community-based individuals without overt cardiovascular disease at baseline, higher MCP-1 levels were associated with increased long-term cardiovascular mortality. The results were present after adjusting for known vascular risk factors, followed a dose-response pattern, and remained stable after additional adjustments for serum IL-6 and high-sensitivity CRP levels.

Our results add to previous data showing significant associations of MCP-1 levels with cardiovascular mortality after acute coronary syndromes,11,12 by also demonstrating an association with cardiovascular mortality in the general population. While attenuated in the multivariable model, we also found significant associations with risk of CHD and nonfatal myocardial infarction in models adjusted for age, sex, and race/ethnicity.

The magnitude of the examined associations was modest, and there was no increment in C-statistics for MCP-1 on top of other vascular risk factors for prognosticating cardiovascular disease. Thus, MCP-1 measurement is unlikely to be a valuable risk marker for cardiovascular end points. However, the aim of this study was to provide additional support for MCP-1 as a promising therapeutic target in atherosclerosis. In fact, the point estimates of the associations with CHD and nonfatal myocardial infarction matched those previously obtained for genetically predicted MCP-1 levels.6 Together, the genetic and biomarker findings support a key role of MCP-1 signaling in cardiovascular disease.

Most studies in this analysis used a broader definition of cardiovascular death that included death from ischemic heart disease, stroke, and other vascular conditions. The more prominent associations compared with CHD and nonfatal myocardial infarction might be explained by differences in the effects of MCP-1 across different vascular beds, in line with our previous findings for stronger associations with stroke.6,9 The observed outcomes of MCP-1 on cardiovascular mortality might be further associated with additive outcomes of MCP-1 on atherosclerosis risk7,8,13,14 and inflammatory responses critical to healing from myocardial infarction.15

Limitations

As a limitation, the lack of a standardized assay to quantify MCP-1 and the differences in assays between studies precluded analyses using absolute MCP-1 values. While previous studies have shown available anti-inflammatory medications to differentially influence MCP-1 levels,16 this could not be examined in this meta-analysis.

Conclusions

In conclusion, higher circulating levels of MCP-1 are associated with higher long-term cardiovascular mortality in community-based individuals free of overt cardiovascular disease. Our findings triangulate previous genetic and experimental evidence supporting a key role of MCP-1-signaling in cardiovascular disease.

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Article Information

Accepted for Publication: August 14, 2020.

Published Online: November 4, 2020. doi:10.1001/jamacardio.2020.5392

Corresponding Author: Martin Dichgans, MD, Institute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-University (LMU), Feodor-Lynen-Str. 17, 81377 Munich, Germany (martin.dichgans@med.uni-muenchen.de).

Author Contributions: Drs Georgakis and Dichgans 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: Georgakis, de Lemos, Myint, Dichgans.

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

Drafting of the manuscript: Georgakis, Sun, Dichgans.

Critical revision of the manuscript for important intellectual content: Georgakis, de Lemos, Ayers, Wang, Björkbacka, Pana, Thorand, Fani, Malik, Dupuis, Engström, Orho-Melander, Melander, Boekholdt, Zierer, Elhadad, Koenig, Herder, Hoogeveen, Kavousi, Ballantyne, Peters, Myint, Nilsson, Benjamin, Dichgans.

Statistical analysis: Georgakis, Ayers, Wang, Björkbacka, Pana, Sun, Fani, Malik, Dupuis, Zierer, Hoogeveen.

Obtained funding: Georgakis, Thorand, Engström, Orho-Melander, Melander, Herder, Nilsson, Benjamin.

Administrative, technical, or material support: Georgakis, Melander, Elhadad, Koenig, Hoogeveen, Myint, Nilsson.

Supervision: Thorand, Koenig, Kavousi, Peters, Myint.

Conflict of Interest Disclosures: Dr de Lemos reports research grants from Abbott Diagnostics and Roche Diagnostics, consulting fees from Ortho Clinical Diagnostics and Janssen, honoraria for steering committee membership from Amgen, data safety monitoring board membership from Novo Nordisk and Regeneron, and personal fees from Eli Lilly outside the submitted work. Dr Koenig reports personal fees from AstraZeneca, Novartis, DalCor, Kowa, Amgen, Corvidia, Daiichi-Sankyo, Sanofi, Pfizer, the Medicines Company, Berlin-Chemie, and Bristol Myers Squibb and grants and nonfinancial support from Roche Diagnostics, Beckmann, Singulex, and Abbott outside the submitted work. Dr Herder reports a research grant from Sanofi outside the submitted work. Dr Ayers reports statistical consulting fees from the National Institutes of Health outside the submitted work. Dr Hoogeveen reports research grants and personal fees for consulting from Denka Seiken. Dr Dupuis reported grants from National Institute of Health during the conduct of the study. Dr Zierer reported grants from Else Kröner–Fresenius Stiftung during the conduct of the study. Dr Hoogeveen reported grants and personal fees from Denka Seiken outside the submitted work. Dr Ballantyne reported grants from the National Institutes of Health during the conduct of the study. Dr Benjamin reported grants from the National Institutes of Health during the conduct of the study. No other disclosures were reported.

Funding/Support: Dr Georgakis has received funding from the Onassis Foundation and the German Academic Exchange Service. The Atherosclerosis Risk in Communities study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, (contracts HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, and HHSN268201700004I). The Dallas Heart Study was funded by a grant from the Donald W. Reynolds Foundation. The European Prospective Investigation Into Cancer in Norfolk Prospective Population study has received funding from the Medical Research Council (grants MR/N003284/1 and MC-UU_12015/1) and Cancer Research UK (grant C864/A14136). The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute in collaboration with Boston University (contracts N01-HC-25195, HHSN268201500001I, and 75N92019D00031) and is additionally supported by grants from the National Institute of Aging and the National Institute of Neurological Disorders and Stroke (grants RO1 HL 064753, RO1 HL076784, and R01 AG028321). The Monitoring of Trends and Determinants in Cardiovascular Disease–Kooperative Gesundheitsforschung in der Region Augsburg study was initiated and financed by the Helmholtz Zentrum München–German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research and the state of Bavaria. Support for the establishment of the case-cohort study and MCP-1 measurements was obtained through a grant from the German Research Foundation (grants TH-784/2-1 and TH-784/2-2) and additional funds provided by the University of Ulm, the Federal Ministry of Health, the Ministry of Innovation, Science, Research and Technology of the state North Rhine–Westphalia. Data analysis was supported by funding from the Helmholtz Alliance “Aging and Metabolic Programming.” The German Diabetes Center is funded by the German Federal Ministry of Health, the Ministry of Culture and Science of the state of North Rhine–Westphalia, and grants from the Federal Ministry of Education and Research. The Malmö Diet and Cancer Study–Cardiovascular Subcohort study has been supported with funding from the Swedish Research Council, Swedish Heart and Lung Foundations, and the Swedish Foundation for Strategic Research. This project has received funding from the European Union’s Horizon 2020 research and innovation programme (grant 666881), SVDs@target (to Dr Dichgans; grant 667375), CoSTREAM (to Dr Dichgans); the German Research Foundation as part of the Munich Cluster for Systems Neurology (grant EXC 2145 SyNergy, ID 390857198) and the Collaborative Research Center 1123 (B3; to Dr Dichgans); the Corona Foundation (to Dr Dichgans); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain; to Dr Dichgans); the e:Med program (e:AtheroSysMed; to Dr Dichgans) and the European Union project CVgenes@target (project FP7/2007-2103; grant agreement number Health-F2-2013-601456; to Dr Dichgans).

Role of the Funder/Sponsor: The funders 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.

Additional Contributions: The authors thank the staff and participants of all the included studies for their important contributions.

References
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