Abstract Body (Do not enter title and authors here): Background: Lipoprotein(a) [Lp(a)], remnant cholesterol (RC), and high-sensitivity C-reactive protein (hsCRP), a marker of systemic inflammation, are emerging non-traditional biomarkers for cardiovascular (CV) risk stratification and treatment guidance. Each of these biomarkers may reflect a distinct but complementary pathway contributing to atherosclerosis and cardiovascular disease (CVD). Therefore, an approach that combines all three may improve the predictive power for CV risk assessment.
Research Question: To what extent does a multi-marker approach combining Lp(a), RC, and hsCRP improve prediction of first myocardial (MI) compared to the use of each biomarker individually?
Methods: We analyzed data from 306,183 participants in the UK Biobank who were free of CVD at baseline and had available measurements for Lp(a), RC, and hsCRP. RC was calculated as total cholesterol minus LDL-C and HDL-C. We examined the cumulative effect of biomarker burden, defined as the number of biomarkers in the highest quintile (0 to 3). We also used Cox proportional hazards models to assess hazard ratios (HRs) and 95% confidence intervals (CIs) for MI risk across biomarker quintiles, adjusted for conventional CV risk factors and the other two biomarkers.
Results: The mean baseline age was 56.4 years; 54.7% were women. Over a 15-year median follow-up, 10,824 MI events occurred (3.5%). There was a graded increase in MI incidence with a rising number of biomarkers in the top quintile (Figure). Adjusted HRs for MI comparing the top versus bottom quintiles were 1.09 (95% CI: 1.08–1.11) for Lp(a), 1.14 (1.13–1.16) for RC, and 1.08 (1.06–1.10) for hsCRP. Relative to individuals with no biomarkers in the top quintile, HRs for MI among those with one, two, or all three biomarkers in the top quintile were 1.45 (1.39–1.51), 2.14 (2.02–2.26), and 2.83 (2.48–3.24), respectively (Table).
Conclusions: Among adults in the UK Biobank without baseline CVD, a multi-marker approach incorporating lipoprotein(a), remnant cholesterol, and high-sensitivity C-reactive protein was associated with a stepwise increase in first myocardial infarction risk corresponding to greater biomarker burden. These findings support the potential value of integrative risk stratification approaches in primary prevention. Further research is warranted to determine whether this multi-marker strategy can inform treatment decisions or improve outcomes.