The interaction between early life epilepsy and autistic-like behavioral consequences: a role for the mammalian target of rapamycin (mTOR) pathway.

Early life seizures can result in chronic epilepsy, cognitive deficits and behavioral changes such as autism, and conversely epilepsy is common in autistic children. We hypothesized that during early brain development, seizures could alter regulators of synaptic development and underlie the interaction between epilepsy and autism. The mammalian Target of Rapamycin (mTOR) modulates protein translation and is dysregulated in Tuberous Sclerosis Complex, a disorder characterized by epilepsy and autism. We used a rodent model of acute hypoxia-induced neonatal seizures that results in long term increases in neuronal excitability, seizure susceptibility, and spontaneous seizures, to determine how seizures alter mTOR Complex 1 (mTORC1) signaling. We hypothesized that seizures occurring at a developmental stage coinciding with a critical period of synaptogenesis will activate mTORC1, contributing to epileptic networks and autistic-like behavior in later life. Here we show that in the rat, baseline mTORC1 activation peaks during the first three postnatal weeks, and induction of seizures at postnatal day 10 results in further transient activation of its downstream targets phospho-4E-BP1 (Thr37/46), phospho-p70S6K (Thr389) and phospho-S6 (Ser235/236), as well as rapid induction of activity-dependent upstream signaling molecules, including BDNF, phospho-Akt (Thr308) and phospho-ERK (Thr202/Tyr204). Furthermore, treatment with the mTORC1 inhibitor rapamycin immediately before and after seizures reversed early increases in glutamatergic neurotransmission and seizure susceptibility and attenuated later life epilepsy and autistic-like behavior. Together, these findings suggest that in the developing brain the mTORC1 signaling pathway is involved in epileptogenesis and altered social behavior, and that it may be a target for development of novel therapies that eliminate the progressive effects of neonatal seizures.

Prediction of fat-free mass and percentage of body fat in neonates using bioelectrical impedance analysis and anthropometric measures: validation against the PEA POD.

Accurate assessment of neonatal body composition is essential to studies investigating neonatal nutrition or developmental origins of obesity. Bioelectrical impedance analysis or bioimpedance analysis is inexpensive, non-invasive and portable, and is widely used in adults for the assessment of body composition. There are currently no prediction algorithms using bioimpedance analysis in neonates that have been directly validated against measurements of fat-free mass (FFM). The aim of the study was to evaluate the use of bioimpedance analysis for the estimation of FFM and percentage of body fat over the first 4 months of life in healthy infants born at term, and to compare these with estimations based on anthropometric measurements (weight and length) and with skinfolds. The present study was an observational study in seventy-seven infants. Body fat content of infants was assessed at birth, 6 weeks, 3 and 4·5 months of age by air displacement plethysmography, using the PEA POD body composition system. Bioimpedance analysis was performed at the same time and the data were used to develop and test prediction equations for FFM. The combination of weight+sex+length predicted FFM, with a bias of < 100 g and limits of agreement of 6-13 %. Before 3 months of age, bioimpedance analysis did not improve the prediction of FFM or body fat. At 3 and 4·5 months, the inclusion of impedance in prediction algorithms resulted in small improvements in prediction of FFM, reducing the bias to < 50 g and limits of agreement to < 9 %. Skinfold measurements performed poorly at all ages.