Metabolic abnormalities associated with diabetes mellitus, as investigated by gas chromatography and pattern-recognition analysis of profiles of volatile metabolites

• Published in: Clinical chemistry (Baltimore, Md.) Vol. 27; no. 4; pp. 580 - 585
• Main Authors: Rhodes, G, Miller, M, McConnell, ML, Novotny, M
• Format: Journal Article
• Language: English
• Published: England Am Assoc Clin Chem 01.04.1981
• Subjects: Chromatography, Gas - methods; Diabetes Mellitus - urine; Female; Gas Chromatography-Mass Spectrometry - methods; Humans; Male; Pattern Recognition, Automated; Sex Factors
• ISSN: 0009-9147; 1530-8561
• DOI: 10.1093/clinchem/27.4.580

Patterns of volatile metabolites in urine, as obtained by glass-capillary gas chromatography, were investigated by use of a nonparametric pattern-recognition method, in an effort to detect abnormalities associated with diabetes. We used threshold logic unit analysis on a data set consisting of normal subjects and those with diabetes mellitus, and could predict patterns for volatile metabolites as belonging to the proper class in 94.83% of the cases examined. In addition, a feature-extraction algorithm isolated those volatile constituents that are most useful in making the normal/diabetic classification. We used gas chromatography/mass spectrometry to identify important profile constituents. Finally, these same pattern-recognition methods indicated strong sex-related patterns in these volatiles.