Metabolomics signature improves the prediction of cardiovascular events in elderly subjects.
OBJECTIVE
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.


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.
Department of Systems Medicine, University of Rome "Tor Vergata", 00133 Rome, Italy.
S
S
Rizza
Unit of Biostatistics, IRCCS, "Casa Sollievo della Sofferenza" San Giovanni Rotondo, FG, Italy.
M
M
Copetti
Department of Clinical and Experimental Sciences, G. D'Annunzio University, Chieti, Pescara, Italy; Center of Excellence on Aging (Ce.S.I.), University Foundation, Chieti, Italy.
C
C
Rossi
Department of Systems Medicine, University of Rome "Tor Vergata", 00133 Rome, Italy.
M A
MA
Cianfarani
Department of Clinical and Experimental Sciences, G. D'Annunzio University, Chieti, Pescara, Italy; Center of Excellence on Aging (Ce.S.I.), University Foundation, Chieti, Italy.
M
M
Zucchelli
Department of Systems Medicine, University of Rome "Tor Vergata", 00133 Rome, Italy.
A
A
Luzi
Department of Systems Medicine, University of Rome "Tor Vergata", 00133 Rome, Italy.
C
C
Pecchioli
Department of Experimental Medicine and Surgery, University of Rome "Tor Vergata", Rome, Italy.
O
O
Porzio
Department of Systems Medicine, University of Rome "Tor Vergata", 00133 Rome, Italy.
G
G
Di Cola
Center of Excellence on Aging (Ce.S.I.), University Foundation, Chieti, Italy; Department of Experimental Medicine and Surgery, University of Rome "Tor Vergata", Rome, Italy.
A
A
Urbani
Unit of Biostatistics, IRCCS, "Casa Sollievo della Sofferenza" San Giovanni Rotondo, FG, Italy.
F
F
Pellegrini
Department of Systems Medicine, University of Rome "Tor Vergata", 00133 Rome, Italy. Electronic address: federicm@uniroma2.it.
M
M
Federici
D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D015415:Biomarkers / Q000097:blood; D002318:Cardiovascular Diseases / Q000097:blood* / Q000378:metabolism*; D002331:Carnitine / Q000031:analogs & derivatives / Q000097:blood; D016922:Cellular Senescence; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D053858:Metabolic Networks and Pathways; D055432:Metabolomics / Q000379:methods*; D009203:Myocardial Infarction / Q000097:blood; D025341:Principal Component Analysis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D020521:Stroke / Q000097:blood
D015415:Biomarkers; C116917:acylcarnitine; D002331:Carnitine
Aging; MACE; Metabolomic; Mitochondrial dysfunction