Identification of serum lipids and amino acids biomarkers in acute aortic dissection using tissue-informed metabolomics methods

BACKGROUND: Type A aortic dissection represents a critical cardiovascular emergency with high mortality and disability rates and a rising incidence. In addition to clinical management, efforts are directed towards identifying high-risk populations for prompt intervention. While some researchers have utilized blood metabolomics to investigate metabolic indicators of type A aortic dissection, the approach is hindered by significant variability, numerous confounding factors, inconsistent outcomes, and limited reproducibility. In this study, the feasibility and effectiveness of a tissue-informed oriented metabolomics approach which refered to oncological minimal residual disease (MRD) detection was investigated. METHODS: Serum and ascending aortic whole layer tissue were collected from 20 patients diagnosed with type A aortic dissection and 20 organ donor volunteers, serving as the experimental and control groups, respectively. Tissue-informed metabolomics included two steps: The metabolic profiles of ascending aortic tissues from patients with and without dissection were examined using a non-targeted metabolomics approach to identify tissue-specific metabolic differences(step 1). Following this, a targeted metabolomics approach was utilized to confirm and screen metabolites in blood samples from both patient groups based on the tissue metabolomic findings(step 2). RESULTS: The metabolomic profiles of aortic tissues obtained from patients diagnosed with type A aortic dissection were analyzed and found to exhibit significant divergence from those of aortic tissues sourced from individuals without any known health conditions. Disturbances in metabolic pathways, including central carbon metabolism, purine metabolism, and ascorbic acid metabolism, were particularly prominent in this study. Tissues were analyzed for 850 distinct metabolites, with amino acids and their derivatives being the most abundant at 147. Subsequently, the focus shifted to the plasma amino acid composition. Following comparative validation, three metabolites, namely kynurenine, homocysteine, and N-acetylneuraminic acid, were identified as significantly different. CONCLUSION: The findings of this study demonstrate the feasibility and effectiveness of utilizing tissue-informed metabolomics in the identification ofpatient-specific metabolites in type A aortic dissection. Tissue-informed metabolomics identified significant abnormalities in certain metabolic pathways and metabolite levels in patients diagnosed with type A aortic dissection.