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Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
Circulating Cardiovascular Proteomic Associations With Genetics and Disease
Kathryn A McGurk1,2,3, Lara Curran1,2,4, Arunashis Sau1,5
1National Heart and Lung Institute, Imperial College London, United Kingdom (K.A.M., L.C., A.S., F.S.N., B.H., J.S.W.).
Background:
The analysis of the circulating proteome can identify translational modifiers and biomarkers of disease expressivity and severity at a given time point. Here, we explore the relationships between protein measures implicated in cardiovascular disease and whether they mediate causal relationships between cardiovascular risk factors and disease development.
Methods:
To understand the relationships between circulating biomarkers and genetic variants, medications, anthropometric traits, lifestyle factors, imaging-derived measures, and diagnoses of cardiovascular disease, we undertook in-depth analyses of measures of 9 plasma proteins with a priori roles in genetic and structural cardiovascular disease or treatment pathways (ACE2 [angiotensin-converting enzyme 2], ACTA2 [actin alpha 2], ACTN4 [actinin alpha 4], BAG3 [BAG cochaperone 3], BNP [B-type natriuretic peptide], CDKN1A [cyclin-dependent kinase inhibitor 1A], NOTCH1 [neurogenic locus notch homolog protein 1], NT-proBNP [N-terminal pro-B-type natriuretic peptide], and TNNI3 [troponin I]) from the Pharma Proteomics Project of the UK Biobank cohort (over 45 000 participants sampled at recruitment).
Results:
We identified significant variability in circulating proteins with age, sex, ancestry, alcohol intake, smoking, and medication intake. Phenome-wide association studies highlighted the range of cardiovascular clinical features with relationships to protein levels. Genome-wide genetic association studies identified variants near GCKR, APOE, and SERPINA1, that modified multiple circulating protein levels (BAG3, CDKN1A, and NOTCH1). NT-proBNP and BNP levels associated with variants in BAG3. ACE2 levels were increased with a diagnosis of hypertension or diabetes, particularly in females, and were influenced by variants in genes associated with diabetes (HNF1A and HNF4A). Two-sample Mendelian randomization identified ACE2 as protective for systolic blood pressure and type-2 diabetes.
Conclusions:
From a panel of circulating proteins, the results from this observational study provide evidence that ACE2 is causally protective for hypertension and diabetes. This suggests that ACE2 treatment may provide additional protection from these cardiovascular diseases. This study provides an improved understanding of the circulating pathways depicting cardiovascular disease dynamics.
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