BORN AT 27 WEEKS OF GESTATION WITH CLASSICAL PKU: CHALLENGES OF DIETETIC MANAGEMENT IN A VERY PRETERM INFANT

Only few cases of classical phenylketonuria (PKU) in premature infants have been reported. Treatment of these patients is challenging due to the lack of a phenylalanine-free amino acid solution for parenteral infusion. The boy was born at 27 weeks of gestation with a weight of 1000 g (P10). He received parenteral nutrition with a protein intake of 3 g/kg/day. On day 7 he was diagnosed with classical PKU (genotype IVS10-11G>A/IVS12+ 1G>A) due to highly elevated phenylalanine (Phe) level in newborn screening (2800 micromol/L). His maximum plasma Phe level reached 3696 micromol/L. Phe intake was stopped for 4 days. During this time the boy received intravenous glucose and lipids as well as little amounts of Phe-free formula by a nasogastric tube. Due to a deficit of essential amino acids and insufficient growth, a parenteral nutrition rich in branched-chain amino-acids and relatively poor in Phe was added, in order to promote protein synthesis without overloading in Phe. Under this regimen, Phe plasma levels normalized on day 19 when intake of natural protein was started. The boy has now a corrected age of 2 years. He shows normal growth parameters and psychomotor development. Despite a long period of highly elevated Phe levels in the postnatal period our patient shows good psychomotor development. The management of premature infants with PKU depends on the child's tolerance to enteral nutrition. It demands an intensive follow-up by an experienced team and dedicated dietician. Appropriate Phe-free parenteral nutrition would be necessary especially in case of gastro-intestinal complications of prematurity.

NEUROPATHOPHYSIOLOGICAL MECHANISMS IN GLUTARIC ACIDURIA TYPE I: 3-HYDROXYGLUTARIC ACID LEADS TO AMMONIA INCREASE AND NON-APOPTOTIC CELL DEATH

A 3D in vitro model of rat organotypic brain cell cultures in aggregates was used to investigate neurotoxicity mechanisms in glutaric aciduria type I (GA-I). 1 mM glutarate (GA) or 3-hydroxyglutarate (3OHGA) were repeatedly added to the culture media at two different time points. In cultures treated with 3OHGA, we observed an increase in lactate in the medium, pointing to a possible inhibition of Krebs cycle and respiratory chain. We further observed that 3OHGA and to a lesser extend GA induced an increase in ammonia production with concomitant decrease of glutamine concentrations, which may suggest an inhibition of the astrocytic enzyme glutamine synthetase. These previously unreported findings may uncover a pathogenic mechanism in this disease which has deleterious effects on early stages of brain development. By immunohistochemistry we showed that 3OHGA increased non-apoptotic cell death. On the cellular level, 3OHGA and to a lesser extend GA led to cell swelling and loss of astrocytic fibers whereas a loss of oligodendrocytes was only observed for 3OHGA. We conclude that 3OHGAwas the most toxic metabolite in our model for GA-I. 3OHGA induced deleterious effects on glial cells, an increase of ammonia production, and resulted in accentuated cell death of non-apoptotic origin.

Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.