bioRxivImmunologyPreprint
Identification and characterization of a human antibody profile inversely associated with adverse cardiovascular events
David M HensoniD, Katherine L. ThompsoniD, Ayman Samman Tahhan, Ryan Marion, Tabarak Azawi, Peng Yeh, Gregory S. HawkiD, Andrew Paul DeFilippisiD, Arshed Ali QuyyumiiD, Vincent J. VendittoiD
Abstract
Objective: The immune response is linked to the progression of atherosclerotic cardiovascular disease (CVD). We sought to characterize a predictive cardiovascular antibody biomarker using two independent cohorts. Approach and Results: A human IgG profile serendipitously identified by ELISA was quantified in a well characterized cohort of 359 patients with a history of coronary artery disease (CAD) who experienced a total of 71 incident adverse CVD events (death, myocardial infarction, and stroke) over a median 4.1-year follow-up. Using Cox proportional hazard regression analysis, low biomarker levels were an independent predictor of adverse cardiovascular outcomes after adjustment for age, sex, diabetes mellitus, estimated glomerular filtration rate, presence of obstructive CAD, heart failure, total cholesterol, and high-density lipoprotein (HDL) cholesterol (adjusted hazard ratio of 1.90 [95% CI: 1.03 to 3.49; p=0.038] between lowest and highest tertiles). Validation was then performed in a larger secondary cohort using 4356 baseline samples from the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of cardiovascular outcomes resulting in adjusted odds ratio of 50.5 per unit decrease in log-transformed biomarker [95% CI: 2.4 to 2773.1; p=0.030] over one year by logistic regression analysis. Conclusions: Low levels of human IgG antibodies targeting Bovidae IgG are independently associated with increased incidence of CVD events in patients with or without a history of CAD, indicating the potential clinical predictive power of this antibody profile as an inverse biomarker for CVD.
- organism: human
- assay: proteomics
- research focus: host-pathogen & immune response
- approach: statistical model
- Citations
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