title: Rapid screening of classic galactosemia patients: a proof-of-concept study using high-throughput FTIR analysis of plasma.
abstract: Classic galactosemia is an autosomal recessive metabolic disease involving the galactose pathway, caused by the deficiency of galactose-1-phosphate uridyltransferase. Galactose accumulation induces in newborns many symptoms, such as liver disease, cataracts, and sepsis leading to death if untreated. Neonatal screening is developed and applied in many countries using several methods to detect galactose or its derived product accumulation in blood or urine. High-throughput FTIR spectroscopy was investigated as a potential tool in the current screening methods. IR spectra were obtained from blood plasma of healthy, diabetic, and galactosemic patients. The major spectral differences were in the carbohydrate region, which was first analysed in an exploratory manner using principal component analysis (PCA). PCA score plots showed a clear discrimination between diabetic and galactosemic patients and this was more marked as a function of the glucose and galactose increased concentration in these patients' plasma respectively. Then, a support vector machine leave-one-out cross-validation (SVM-LOOCV) classifier was built with the PCA scores as the input and the model was tested on median, mean and all spectra from the three population groups. This classifier was able to discriminate healthy/diabetic, healthy/galactosemic, and diabetic/galactosemic patients with sensitivity and specificity rates ranging from 80% to 94%. The total accuracy rate ranged from 87% to 96%. High-throughput FTIR spectroscopy combined with the SVM-LOOCV classification procedure appears to be a promising tool in the screening of galactosemia patients, with good sensitivity and specificity. Furthermore, this approach presents the advantages of being cost-effective, fast, and straightforward in the screening of galactosemic patients.
authors.affiliation: Université de Reims Champagne-Ardenne, Equipe MéDIAN, Biophotonique et Technologies pour la Santé, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096 Reims, France. caroline_lacombe@hotmail.fr valerie.untereiner@univ-reims.fr cyril.gobinet@univ-reims.fr ganesh.sockalingum@univ-reims.fr.
authors.forename: Caroline
authors.initials: C
authors.lastname: Lacombe
authors.forename: Valérie
authors.initials: V
authors.lastname: Untereiner
authors.forename: Cyril
authors.initials: C
authors.lastname: Gobinet
authors.forename: Mokhtar
authors.initials: M
authors.lastname: Zater
authors.forename: Ganesh D
authors.initials: GD
authors.lastname: Sockalingum
authors.forename: Roselyne
authors.initials: R
authors.lastname: Garnotel
mesh_terms: D000328:Adult; D002648:Child; D002675:Child, Preschool; D003920:Diabetes Mellitus / Q000097:blood; D005240:Feasibility Studies; D005260:Female; D005693:Galactosemias / Q000097:blood* / Q000175:diagnosis*; D006801:Humans; D007223:Infant; D008297:Male; D025341:Principal Component Analysis; D017550:Spectroscopy, Fourier Transform Infrared; D060388:Support Vector Machine