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Ward-Caviness, C.K. ; Xu, T. ; Aspelund, T.* ; Thorand, B. ; Montrone, C. ; Meisinger, C. ; Dunger-Kaltenbach, I. ; Zierer, A. ; Yu, Z. ; Helgadottir, I.R.* ; Harris, T.B.* ; Launer, L.J.* ; Ganna, A.* ; Lind, L.* ; Eiriksdottir, G.* ; Waldenberger, M. ; Prehn, C. ; Suhre, K. ; Illig, T.* ; Adamski, J. ; Ruepp, A. ; Koenig, W.* ; Gudnason, V.* ; Emilsson, V.* ; Wang-Sattler, R. ; Peters, A.

Improvement of myocardial infarction risk prediction via inflammation-associated metabolite biomarkers.

Heart 103, 1278-1285 (2017)

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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

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OBJECTIVE: The comprehensive assaying of low-molecular-weight compounds, for example, metabolomics, provides a unique tool to uncover novel biomarkers and understand pathways underlying myocardial infarction (MI). We used a targeted metabolomics approach to identify biomarkers for MI and evaluate their involvement in the pathogenesis of MI. METHODS AND RESULTS: Using three independent, prospective cohorts (KORA S4, KORA S2 and AGES-REFINE), totalling 2257 participants without a history of MI at baseline, we identified metabolites associated with incident MI (266 cases). We also investigated the association between the metabolites and high-sensitivity C reactive protein (hsCRP) to understand the relation between these metabolites and systemic inflammation. Out of 140 metabolites, 16 were nominally associated (p<0.05) with incident MI in KORA S4. Three metabolites, arginine and two lysophosphatidylcholines (LPC 17:0 and LPC 18:2), were selected as biomarkers via a backward stepwise selection procedure in the KORA S4 and were significant (p<0.0003) in a meta-analysis comprising all three studies including KORA S2 and AGES-REFINE. Furthermore, these three metabolites increased the predictive value of the Framingham risk score, increasing the area under the receiver operating characteristic score in KORA S4 (from 0.70 to 0.78, p=0.001) and AGES-REFINE study (from 0.70 to 0.76, p=0.02), but was not observed in KORA S2. The metabolite biomarkers attenuated the association between hsCRP and MI, indicating a potential link to systemic inflammatory processes. CONCLUSIONS: We identified three metabolite biomarkers, which in combination increase the predictive value of the Framingham risk score. The attenuation of the hsCRP-MI association by these three metabolites indicates a potential link to systemic inflammation.

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