Urinary metabolic profiling of asymptomatic acute intermittent porphyria using a rule-mining-based algorithm

使用基于规则挖掘的算法对无症状急性间歇性卟啉症进行尿液代谢分析

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作者:Margaux Luck, Caroline Schmitt, Neila Talbi, Laurent Gouya, Cédric Caradeuc, Hervé Puy, Gildas Bertho, Nicolas Pallet2

Conclusion

These results suggest that metabolic reprogramming occurs in aAIP individuals, even in the absence of overt symptoms, and supports the relationship that occur between heme synthesis and mitochondrial energetic metabolism.

Methods

Urine 1H-NMR spectra of 73 patients with asymptomatic acute intermittent porphyria (aAIP) and familial or sporadic porphyria cutanea tarda (f/sPCT) were compared using a supervised rule-mining algorithm. NMR spectrum buckets bins, corresponding to rules, were extracted and a logistic regression was trained.

Results

Our rule-mining algorithm generated results were consistent with those obtained using partial least square discriminant analysis (PLS-DA) and the predictive performance of the model was significant. Buckets that were identified by the algorithm corresponded to metabolites involved in glycolysis and energy-conversion pathways, notably acetate, citrate, and pyruvate, which were found in higher concentrations in the urines of aAIP compared with PCT patients. Metabolic profiling did not discriminate sPCT from fPCT patients.

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