A survey on inborn errors of metabolism in 323 neonates from the state of Rio de Janeiro, Brazil

Inborn errors of metabolism (IEM) are a relevant cause of morbidity and death among children, and neonates in particular. However, little is known about the prevalence of these disorders in Brazilian newborns. Our laboratory of IEM (LABEIM) at the Department of Biochemistry, Institute of Chemistry, Federal University of Rio de Janeiro (UFRJ), has been working on the diagnosis of IEM since 1988. Out of 3,300 patients (90% children), screened and evaluated from 1989 to 2,000 because of a high clinical suspicion of having an IEM, 323 (9.8%) were neonates. Patients came from different regions of the state of Rio de Janeiro, in which lives approximately 8.5% of the total Brazilian population. Chemical tests, various chromatographic techniques and enzyme assays were performed in urine, plasma and in some cases, cerebrospinal fluid (CSF). This study describes our laboratory and the experience with the 323 investigated neonates, among which 28 cases (8.7%) of IEM were identified and 18 (5.6%), strongly suspected. All these cases were related mainly to the metabolism of amino acids, organic acids, lysosomal enzymes and carbohydrates. Furthermore, data on population, community and health services are presented.     

Metabolite Fingerprinting Using 1H-NMR Spectroscopy and Chemometrics for Classification of Three Curcuma Species from Different Origins

Curcuma longa, Curcuma xanthorrhiza, and Curcuma manga have been widely used for herbal or traditional medicine purposes. It was reported that turmeric plants provided several biological activities such as antioxidant, anti-inflammatory, hepatoprotector, cardioprotector, and anticancer activities. Authentication of the Curcuma species is important to ensure its authenticity and to avoid adulteration practices. Plants from different origins will have different metabolite compositions because metabolites are affected by soil nutrition, climate, temperature, and humidity. ¹H-NMR spectroscopy, principal component analysis (PCA), and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for authentication of C. longa, C. xanthorrhiza, and C. manga from seven different origins in Indonesia. From the ¹H-NMR analysis it was obtained that 14 metabolites were responsible for generating classification model such as curcumin, demethoxycurcumin, alanine, methionine, threonine, lysine, alpha-glucose, beta-glucose, sucrose, alpha-fructose, beta-fructose, fumaric acid, tyrosine, and formate. Both PCA and OPLS-DA model demonstrated goodness of fit (R² value more than 0.8) and good predictivity (Q² value more than 0.45). All OPLS-DA models were validated by assessing the permutation test results with high value of original R² and Q². It can be concluded that metabolite fingerprinting using ¹H-NMR spectroscopy and chemometrics provide a powerful tool for authentication of herbal and medicinal plants.