Metabolomics signature improves the prediction of cardiovascular events in elderly subjects

Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails great challenge. A possible explanation of vascular senescence process is the mitochondrial damage and dysfunction. We hypothesized that metabol...

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Published inAtherosclerosis Vol. 232; no. 2; pp. 260 - 264
Main Authors Rizza, S., Copetti, M., Rossi, C., Cianfarani, M.A., Zucchelli, M., Luzi, A., Pecchioli, C., Porzio, O., Di Cola, G., Urbani, A., Pellegrini, F., Federici, M.
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LanguageEnglish
Published Ireland Elsevier Ireland Ltd 01.02.2014
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Abstract Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails great challenge. A possible explanation of vascular senescence process is the mitochondrial damage and dysfunction. We hypothesized that metabolomic profiling would identify biomarkers predicting major cardiovascular events (MACEs) in elderly people, improving the clinical standard cardiovascular risk factors. Targeted-mass-spectrometry-based profiling of 49 metabolites was performed in a group of very old participants (n = 67, mean age = 85 ± 3 years) with a high rate of previous CVD (68%). Principal Component Analysis, Random Survival Forest analysis and Cox proportional hazards regression modeling were used to evaluate the relation between the metabolite factors and recurring MACEs. We tested discrimination ability and reclassification of clinical and metabolomic models. At follow-up (median = 3.5 years), 17 MACEs occurred (5 cardiovascular deaths, 1 nonfatal myocardial infarction, 7 nonfatal strokes and 4 peripheral artery surgeries) (incidence = 7.3% person-years). Metabolite factor 1, composed by medium- and long-chain acylcarnitines, and factor 7 (alanine) were independently associated with MACEs, after adjustment for clinical CV covariates [HR = 1.77 (95%CI = 1.11–2.81, p = 0.016) and HR = 2.18 (95%CI = 1.17–4.07, p = 0.014), respectively]. However, only factor 1 significantly increases the prediction accuracy of the Framingham Recurring-Coronary-Heart-Disease-Score, with a significant improvement in discrimination (integrated discrimination improvement = 7%, p = 0.01) and correctly reclassifying 41% of events and 37% of non-events resulting in a cNRI = 0.79 (p = 0.005). Aging mitochondrial dysfunction evaluated by metabolomic profiling is associated with MACEs, independently of standard predictors. •Aging is associated to increased CV risk.•Metabolic pathways confer CV risk.•Metabolomics can be used to map metabolic pathways in vivo.•Acyl-carnitines predict major cardiovascular event in older people.•Recurrent Framingham score is improved by acyl-carnitine.
AbstractList Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails great challenge. A possible explanation of vascular senescence process is the mitochondrial damage and dysfunction. We hypothesized that metabolomic profiling would identify biomarkers predicting major cardiovascular events (MACEs) in elderly people, improving the clinical standard cardiovascular risk factors. Targeted-mass-spectrometry-based profiling of 49 metabolites was performed in a group of very old participants (n = 67, mean age = 85 ± 3 years) with a high rate of previous CVD (68%). Principal Component Analysis, Random Survival Forest analysis and Cox proportional hazards regression modeling were used to evaluate the relation between the metabolite factors and recurring MACEs. We tested discrimination ability and reclassification of clinical and metabolomic models. At follow-up (median = 3.5 years), 17 MACEs occurred (5 cardiovascular deaths, 1 nonfatal myocardial infarction, 7 nonfatal strokes and 4 peripheral artery surgeries) (incidence = 7.3% person-years). Metabolite factor 1, composed by medium- and long-chain acylcarnitines, and factor 7 (alanine) were independently associated with MACEs, after adjustment for clinical CV covariates [HR = 1.77 (95%CI = 1.11–2.81, p = 0.016) and HR = 2.18 (95%CI = 1.17–4.07, p = 0.014), respectively]. However, only factor 1 significantly increases the prediction accuracy of the Framingham Recurring-Coronary-Heart-Disease-Score, with a significant improvement in discrimination (integrated discrimination improvement = 7%, p = 0.01) and correctly reclassifying 41% of events and 37% of non-events resulting in a cNRI = 0.79 (p = 0.005). Aging mitochondrial dysfunction evaluated by metabolomic profiling is associated with MACEs, independently of standard predictors. •Aging is associated to increased CV risk.•Metabolic pathways confer CV risk.•Metabolomics can be used to map metabolic pathways in vivo.•Acyl-carnitines predict major cardiovascular event in older people.•Recurrent Framingham score is improved by acyl-carnitine.
Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails great challenge. A possible explanation of vascular senescence process is the mitochondrial damage and dysfunction. We hypothesized that metabolomic profiling would identify biomarkers predicting major cardiovascular events (MACEs) in elderly people, improving the clinical standard cardiovascular risk factors. Targeted-mass-spectrometry-based profiling of 49 metabolites was performed in a group of very old participants (n = 67, mean age = 85 ± 3 years) with a high rate of previous CVD (68%). Principal Component Analysis, Random Survival Forest analysis and Cox proportional hazards regression modeling were used to evaluate the relation between the metabolite factors and recurring MACEs. We tested discrimination ability and reclassification of clinical and metabolomic models. At follow-up (median = 3.5 years), 17 MACEs occurred (5 cardiovascular deaths, 1 nonfatal myocardial infarction, 7 nonfatal strokes and 4 peripheral artery surgeries) (incidence = 7.3% person-years). Metabolite factor 1, composed by medium- and long-chain acylcarnitines, and factor 7 (alanine) were independently associated with MACEs, after adjustment for clinical CV covariates [HR = 1.77 (95%CI = 1.11-2.81, p = 0.016) and HR = 2.18 (95%CI = 1.17-4.07, p = 0.014), respectively]. However, only factor 1 significantly increases the prediction accuracy of the Framingham Recurring-Coronary-Heart-Disease-Score, with a significant improvement in discrimination (integrated discrimination improvement = 7%, p = 0.01) and correctly reclassifying 41% of events and 37% of non-events resulting in a cNRI = 0.79 (p = 0.005). Aging mitochondrial dysfunction evaluated by metabolomic profiling is associated with MACEs, independently of standard predictors.
Abstract Aims Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails great challenge. A possible explanation of vascular senescence process is the mitochondrial damage and dysfunction. We hypothesized that metabolomic profiling would identify biomarkers predicting major cardiovascular events (MACEs) in elderly people, improving the clinical standard cardiovascular risk factors. Methods and results Targeted-mass-spectrometry-based profiling of 49 metabolites was performed in a group of very old participants ( n  = 67, mean age = 85 ± 3 years) with a high rate of previous CVD (68%). Principal Component Analysis, Random Survival Forest analysis and Cox proportional hazards regression modeling were used to evaluate the relation between the metabolite factors and recurring MACEs. We tested discrimination ability and reclassification of clinical and metabolomic models. At follow-up (median = 3.5 years), 17 MACEs occurred (5 cardiovascular deaths, 1 nonfatal myocardial infarction, 7 nonfatal strokes and 4 peripheral artery surgeries) (incidence = 7.3% person-years). Metabolite factor 1, composed by medium- and long-chain acylcarnitines, and factor 7 (alanine) were independently associated with MACEs, after adjustment for clinical CV covariates [HR = 1.77 (95%CI = 1.11–2.81, p  = 0.016) and HR = 2.18 (95%CI = 1.17–4.07, p  = 0.014), respectively]. However, only factor 1 significantly increases the prediction accuracy of the Framingham Recurring - Coronary-Heart-Disease-Score , with a significant improvement in discrimination (integrated discrimination improvement = 7%, p  = 0.01) and correctly reclassifying 41% of events and 37% of non-events resulting in a cNRI = 0.79 ( p  = 0.005). Conclusions Aging mitochondrial dysfunction evaluated by metabolomic profiling is associated with MACEs, independently of standard predictors.
Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails great challenge. A possible explanation of vascular senescence process is the mitochondrial damage and dysfunction. We hypothesized that metabolomic profiling would identify biomarkers predicting major cardiovascular events (MACEs) in elderly people, improving the clinical standard cardiovascular risk factors.AIMSAge is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails great challenge. A possible explanation of vascular senescence process is the mitochondrial damage and dysfunction. We hypothesized that metabolomic profiling would identify biomarkers predicting major cardiovascular events (MACEs) in elderly people, improving the clinical standard cardiovascular risk factors.Targeted-mass-spectrometry-based profiling of 49 metabolites was performed in a group of very old participants (n = 67, mean age = 85 ± 3 years) with a high rate of previous CVD (68%). Principal Component Analysis, Random Survival Forest analysis and Cox proportional hazards regression modeling were used to evaluate the relation between the metabolite factors and recurring MACEs. We tested discrimination ability and reclassification of clinical and metabolomic models. At follow-up (median = 3.5 years), 17 MACEs occurred (5 cardiovascular deaths, 1 nonfatal myocardial infarction, 7 nonfatal strokes and 4 peripheral artery surgeries) (incidence = 7.3% person-years). Metabolite factor 1, composed by medium- and long-chain acylcarnitines, and factor 7 (alanine) were independently associated with MACEs, after adjustment for clinical CV covariates [HR = 1.77 (95%CI = 1.11-2.81, p = 0.016) and HR = 2.18 (95%CI = 1.17-4.07, p = 0.014), respectively]. However, only factor 1 significantly increases the prediction accuracy of the Framingham Recurring-Coronary-Heart-Disease-Score, with a significant improvement in discrimination (integrated discrimination improvement = 7%, p = 0.01) and correctly reclassifying 41% of events and 37% of non-events resulting in a cNRI = 0.79 (p = 0.005).METHODS AND RESULTSTargeted-mass-spectrometry-based profiling of 49 metabolites was performed in a group of very old participants (n = 67, mean age = 85 ± 3 years) with a high rate of previous CVD (68%). Principal Component Analysis, Random Survival Forest analysis and Cox proportional hazards regression modeling were used to evaluate the relation between the metabolite factors and recurring MACEs. We tested discrimination ability and reclassification of clinical and metabolomic models. At follow-up (median = 3.5 years), 17 MACEs occurred (5 cardiovascular deaths, 1 nonfatal myocardial infarction, 7 nonfatal strokes and 4 peripheral artery surgeries) (incidence = 7.3% person-years). Metabolite factor 1, composed by medium- and long-chain acylcarnitines, and factor 7 (alanine) were independently associated with MACEs, after adjustment for clinical CV covariates [HR = 1.77 (95%CI = 1.11-2.81, p = 0.016) and HR = 2.18 (95%CI = 1.17-4.07, p = 0.014), respectively]. However, only factor 1 significantly increases the prediction accuracy of the Framingham Recurring-Coronary-Heart-Disease-Score, with a significant improvement in discrimination (integrated discrimination improvement = 7%, p = 0.01) and correctly reclassifying 41% of events and 37% of non-events resulting in a cNRI = 0.79 (p = 0.005).Aging mitochondrial dysfunction evaluated by metabolomic profiling is associated with MACEs, independently of standard predictors.CONCLUSIONSAging mitochondrial dysfunction evaluated by metabolomic profiling is associated with MACEs, independently of standard predictors.
Author Rizza, S.
Pellegrini, F.
Di Cola, G.
Zucchelli, M.
Luzi, A.
Urbani, A.
Cianfarani, M.A.
Copetti, M.
Pecchioli, C.
Porzio, O.
Rossi, C.
Federici, M.
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  surname: Luzi
  fullname: Luzi, A.
  organization: Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
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  surname: Pecchioli
  fullname: Pecchioli, C.
  organization: Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
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  surname: Porzio
  fullname: Porzio, O.
  organization: Department of Experimental Medicine and Surgery, University of Rome “Tor Vergata”, Rome, Italy
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  surname: Di Cola
  fullname: Di Cola, G.
  organization: Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
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  organization: Center of Excellence on Aging (Ce.S.I.), University Foundation, Chieti, Italy
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  surname: Federici
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  email: federicm@uniroma2.it
  organization: Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
BackLink https://www.ncbi.nlm.nih.gov/pubmed/24468136$$D View this record in MEDLINE/PubMed
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Elsevier Ireland Ltd
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Issue 2
Keywords Metabolomic
Aging
Mitochondrial dysfunction
MACE
Language English
License Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
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Snippet Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly people entails...
Abstract Aims Age is one of the most important determinants of cardiovascular health, therefore the management of cardiovascular diseases (CVD) in elderly...
SourceID proquest
pubmed
crossref
elsevier
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Publisher
StartPage 260
SubjectTerms Aged
Aged, 80 and over
Aging
Biomarkers - blood
Cardiovascular
Cardiovascular Diseases - blood
Cardiovascular Diseases - metabolism
Carnitine - analogs & derivatives
Carnitine - blood
Cellular Senescence
Female
Follow-Up Studies
Humans
MACE
Male
Metabolic Networks and Pathways
Metabolomic
Metabolomics - methods
Mitochondrial dysfunction
Myocardial Infarction - blood
Principal Component Analysis
Proportional Hazards Models
Reproducibility of Results
Stroke - blood
Title Metabolomics signature improves the prediction of cardiovascular events in elderly subjects
URI https://www.clinicalkey.com/#!/content/1-s2.0-S0021915013006291
https://www.clinicalkey.es/playcontent/1-s2.0-S0021915013006291
https://dx.doi.org/10.1016/j.atherosclerosis.2013.10.029
https://www.ncbi.nlm.nih.gov/pubmed/24468136
https://www.proquest.com/docview/1492719490
Volume 232
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