ACE Phenotyping in Human Blood and Tissues: Revelation of ACE Outliers and Sex Differences in ACE Sialylation.
Enikő E EnyediPavel A PetukhovAlexander J KozuchSteven M DudekAttila TóthMiklós FagyasSergei M DanilovPublished in: Biomedicines (2024)
Angiotensin-converting enzyme (ACE) metabolizes a number of important peptides participating in blood pressure regulation and vascular remodeling. Elevated ACE expression in tissues (which is generally reflected by blood ACE levels) is associated with an increased risk of cardiovascular diseases. Elevated blood ACE is also a marker for granulomatous diseases. Decreased blood ACE activity is becoming a new risk factor for Alzheimer's disease. We applied our novel approach-ACE phenotyping-to characterize pairs of tissues (lung, heart, lymph nodes) and serum ACE in 50 patients. ACE phenotyping includes (1) measurement of ACE activity with two substrates (ZPHL and HHL); (2) calculation of the ratio of hydrolysis of these substrates (ZPHL/HHL ratio); (3) determination of ACE immunoreactive protein levels using mAbs to ACE; and (4) ACE conformation with a set of mAbs to ACE. The ACE phenotyping approach in screening format with special attention to outliers, combined with analysis of sequencing data, allowed us to identify patient with a unique ACE phenotype related to decreased ability of inhibition of ACE activity by albumin, likely due to competition with high CCL18 in this patient for binding to ACE. We also confirmed recently discovered gender differences in sialylation of some glycosylation sites of ACE. ACE phenotyping is a promising new approach for the identification of ACE phenotype outliers with potential clinical significance, making it useful for screening in a personalized medicine approach.
Keyphrases
- angiotensin converting enzyme
- angiotensin ii
- blood pressure
- heart failure
- cardiovascular disease
- gene expression
- endothelial cells
- type diabetes
- risk assessment
- working memory
- rheumatoid arthritis
- systemic sclerosis
- cognitive decline
- atrial fibrillation
- poor prognosis
- coronary artery disease
- newly diagnosed
- high resolution
- simultaneous determination
- ejection fraction
- single cell
- blood glucose
- protein protein
- deep learning
- case report
- prognostic factors
- bioinformatics analysis
- tandem mass spectrometry