Why the study?
Biomarkers of myocardial fibrosis and inflammation have been individually linked to LVH and diastolic dysfunction, but the added value of a combined multimarker approach in a population setting remained unstudied.
Does a multimarker approach (BNP, Gal3, P3NP, ST2) improve the detection of left ventricular hypertrophy and diastolic dysfunction compared to clinical variables alone in a general population cohort?
Does a multimarker approach (BNP, Gal3, P3NP, ST2) improve the detection of left ventricular hypertrophy and diastolic dysfunction compared to clinical variables alone in a general population cohort?
The addition of fibrosis and inflammation biomarkers to routine clinical evaluation provides only marginal improvement in predicting preclinical diastolic dysfunction and left ventricular hypertrophy, and their systematic use for screening is not recommended.
Multimarker fibrosis-inflammation panels add only marginal value for preclinical LVH/DD screening; leaves open whether personalized proteomic-clinical scores merit targeted trials.
Aims Biomarkers reflecting myocardial fibrosis and inflammation have been individually associated with left ventricular hypertrophy (LVH) and diastolic dysfunction (DD). However, the added value of a fibrosis-inflammation multimarker approach in a populational setting is yet to be studied. We evaluated the value of a multimarker approach to detect LVH and DD in a large population-based cohort. Methods and results In a prespecified analysis (BioSe-PreIC study) of the 4th visit of the STANISLAS cohort (1705 subjects, 47 ± 14 years, 47.4% men), we evaluated the ability of brain natriuretic peptide (BNP), Galectin-3 (GAL3), N-terminal propeptide of procollagen type III (P3NP), and soluble ST2 to predict LVH (LV mass > 116/100 g/m2 for men/women) and DD using discrimination (C-index) and reclassification analysis (NRI). Participants with LVH and/or DD had significantly higher levels of BNP, GAL3, and ST2. Overall, the predictive value of clinical variables for LVH and/or DD was good (C-index ranging from 0.76 to 0.82) and the addition of BNP, Gal3, P3NP, and ST2 moderately but significantly improved predictive value (delta C-index = 0.03, P = 0.03 for LVH and 0.01, P = 0.01 for DD) and reclassification (NRI = 25.3, P = 0.02 for LVH and NRI = 32.7 for DD, P < 0.0001). Gal3, P3NP, and ST2 significantly improved predictive value (delta C-index = 0.01, P = 0.01) and reclassification (NRI = 31.3, P < 0.0001) for DD of top of clinical variables and BNP. Conclusions As the measurement of Gal3, P3NP, and ST2 results in marginal (even if significant) increase in the prediction of DD/LVH on top of routine evaluation, their systematic use should not be promoted in unselected healthy individuals to screen for preclinical DD. Further research is needed to determine whether a more personalized medicine approach combing proteomic and clinical scoring can amplify the added value of biomarkers to identify preclinical DD.
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Huttin et al. (2021) studied this question.
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