Clin Res Cardiol (2022).

Associations of SCORE2 and circulating cardiovascular biomarkers - Insights from the population-based Hamburg City Health Study
B. Toprak1, J. Lehmacher1, Y. Hu2, C. Waldeyer1, T. Zeller3, S. Blankenberg1, J. T. Neumann1, R. Twerenbold3, für die Studiengruppe: HCHS
1Klinik für Kardiologie, Universitäres Herz- und Gefäßzentrum Hamburg GmbH, Hamburg; 2Cardio-CARE AG, Davos, Schweiz; 3Klinik für Kardiologie und University Center of Cardiovascular Science, Universitäres Herz- und Gefäßzentrum Hamburg GmbH, Hamburg;

Background: The European Society of Cardiology (ESC) recently published an updated version of the Systematic Coronary Risk Evaluation (SCORE2) model to estimate the 10-year risk of fatal and non-fatal cardiovascular events based on traditional cardiovascular risk factors. Although circulating cardiovascular biomarkers are known to be predictive for incident cardiovascular diseases (CVD) in the general population beyond traditional risk factors, they are still largely missing in long-term risk prediction models such as SCORE2.

Aims: We aimed to assess the correlation of SCORE2 with circulating biomarkers mirroring four distinctive pathophysiological pathways: high-sensitivity troponin I (hs-cTnI) for myocardial injury, N-terminal pro B-type natriuretic peptide (NT-proBNP) for hemodynamic stress, cystatin C and its derived estimated glomerular filtration rate (eGFR CKD-EPI cystatin C) for renal dysfunction and high-sensitivity C-reactive protein (hs-CRP) for inflammatory activity.

Methods: In the first set of 10,000 participants of the prospective, cross-sectional, population-based Hamburg City Health Study (HCHS) recruited between 2016 and 2019, the SCORE2 model was applied to estimate the 10-year risk of CVD. Individuals were categorized into five risk groups (<2.5%, 2- <5%, 5- <10%, 10- <15%, and ≥15%). Individuals with prevalent CVD were excluded. Associations between the continuous SCORE2 risk estimates and circulating biomarkers were estimated using Pearson correlation and illustrated by splines. Biomarker concentrations were log transformed to achieve a more normal distribution, and then winsorized at 2.5% and 97.5% to avoid statistical distortion by outliers.

Results: Of the 8,518 individuals eligible for this analysis, 53.7% were females and median age was 61 years.
 Median estimated 10-year risk of fatal and non-fatal CVD based on SCORE2 was 6.1% (interquartile range [IQR] 3.2-9.9%). Blood concentrations of all investigated biomarkers increased significantly with higher SCORE2 risk group (P<0.001, see Table). All circulating biomarkers correlated highly significantly with the continuous SCORE2 risk (see Figure). Thereby, hs-cTnI (R= 0.42, P<0.001), cystatin C (R= 0.42, P<0.001) and eGFR (R= -0.45, P<0.001) showed a stronger correlation than NT-proBNP (R= 0.21, P<0.001) and hs-CRP (R= 0.22, P<0.001).

Conclusions: All investigated circulating cardiovascular biomarkers depicting different pathophysiological mechanisms correlate well with the long-term cardiovascular risk estimated by SCORE2. Their additive value in future risk models might help to further improve and personalize cardiovascular risk prediction in the general population.

Table. Circulating cardiovascular biomarker levels by SCORE2 risk group.

Figure. Spline regressions for the correlation between circulating biomarkers and SCORE2 risk.