AI Article Synopsis

  • Pulmonary arterial hypertension (PAH) is a serious condition that is often misdiagnosed, prompting a study to compare metabolomic profiles of PAH patients and healthy controls.
  • The study used GC-MS technology to analyze plasma and urine samples, creating a linear discriminant analysis model that classified PAH patients with 91% accuracy based on specific metabolites.
  • Key metabolites identified, including pyruvic acid and butyric acid, could lead to noninvasive testing methods for easier, earlier detection of PAH in patients experiencing dyspnea.

Article Abstract

Pulmonary arterial hypertension (PAH) is a severe, multifactorial, and frequently misdiagnosed disorder. The aim of this observational study was to compare the plasma and urine metabolomic profiles of PAH patients and healthy control subjects. Plasma and urine metabolomic profiles were analyzed using the GC-MS technique. Correlations between metabolite levels and clinical parameters among PAH patients, as well as the between-group differences, were evaluated. The linear discriminant analysis model, which allows for subject classification in terms of PAH with the highest possible precision, was developed and proposed. Plasma pyruvic acid, cholesterol, threonine, urine 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid, butyric acid, 1,2-benzenediol, glucoheptonic acid, and 2-oxo-glutaric acid were found to build a relatively accurate classification model for PAH patients. The model reached an accuracy of 91% and significantly improved subject classification (OR = 119 [95% CI: 20.3-698.3], < 0.0001). Five metabolites were detected in urine that provide easily available and noninvasive tests as compared to right heart catheterization. The selected panel of metabolites has potential for early recognition of patients with dyspnea and faster referral to a reference center.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11302416PMC
http://dx.doi.org/10.1021/acs.jproteome.3c00255DOI Listing

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