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Socioeconomic disparity in cardiovascular disease: Possible biological pathways based on a proteomic approach
Bilal Hasan Shafi1, Morten Bøttcher2, Ali Ejupi1
1Department of Cardiology, Bispebjerg University Hospital, Copenhagen, Denmark.
Insights
Socioeconomic disparities in cardiovascular disease (CVD) are linked to biological pathways. Inflammation, platelet activation, and blood pressure biomarkers may explain these differences, highlighting potential targets for intervention.
Area of Science:
- Biomedical research
- Cardiovascular disease epidemiology
- Biomarker discovery
Background:
- Significant social disparities exist in cardiovascular disease (CVD) occurrence.
- Underlying biological mechanisms driving these disparities remain largely unknown.
Purpose of the Study:
- To investigate biomarkers linked to CVD to understand socioeconomic disparities.
- To quantify biological pathways mediating socioeconomic differences in CVD through risk factors.
Main Methods:
- Analysis of 184 biomarkers in 1142 participants (aged 55-64) from the Copenhagen City Heart Study.
- Socioeconomic position (SEP) defined by education length and household income.
- Statistical analysis including Pearson's correlation and multivariate-adjusted linear regression.
Main Results:
- 48 biomarkers significantly correlated with education length; strongest associations with interleukin-6 (IL-6), GDF-15, RARRES2, leptin (LEP), vWF, and renin (REN).
- 14 biomarkers remained significantly associated with education after multivariate adjustment.
- Proportion mediated by CVD risk factors varied from <1% to 100%.
Conclusions:
- Socioeconomic position is associated with multiple biomarkers, suggesting pathways involving inflammation, platelet activation, blood pressure, and MAPK cascade.
- These pathways may contribute to socioeconomic differences observed in CVD.
- Identified biomarkers offer potential targets for understanding and mitigating CVD disparities.
Background And Aims:
Large social disparities in the occurrence of cardiovascular disease (CVD) have been documented but the underlying biological mechanisms are largely unknown. We investigated a panel of biomarkers linked to CVD to improve our understanding and quantify the biological pathways in socioeconomic disparity in CVD and their mediation through behavioural and biological risk factors.
Methods:
We included 1142 participants from the Copenhagen City Heart Study aged 55-64 years. Socioeconomic position (SEP) was defined by the length of education and household income. Blood samples were analysed for 184 biomarkers (Olink). Pearson's correlation analysis and linear regression with multivariate adjustment for CVD risk factors were performed.
Results:
The median length of education was 10 (IQR 7-11) years and associated with age, sex, BMI, smoking, blood pressure, physical activity and income. 48 biomarkers were significantly correlated (p < 0.05) to the length of education. The strongest negative associations were seen for interleukin-6 (IL-6), metalloproteinase 12, growth/differentiation factor 15 (GDF-15), retinoic acid receptor responder protein 2 (RARRES2), leptin (LEP), von Willebrand factor (vWF), and renin (REN) (all p < 0.0001) while the strongest positive associations were seen for chymotrypsin, paraoxonase, epidermal growth factor receptor (EGFR) and brother of CDO (cell adhesion and platelet activation) (all p < 0.001). Proportion mediated by CVD risk factors ranged from <1% to 100%. After multivariate adjustment, 14 biomarkers remained significantly associated with education.
Conclusions:
SEP was associated with multiple biomarkers, indicating pathways involving inflammation (IL-6, RARRES2), platelet-activation (vWF, IL-6), blood pressure (REN, LEP) and Mitogen-activated protein kinase cascade (GDF-15, EGFR) may contribute to the socioeconomic differences in CVD.
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