Adult cognitive outcomes in phenylketonuria:explaining causes of variability beyond average Phe levels

OBJECTIVE: The objective was to deepen the understanding of the causes of individual variability in phenylketonuria (PKU) by investigating which metabolic variables are most important for predicting cognitive outcomes (Phe average vs Phe variation) and by assessing the risk of cognitive impairment associated with adopting a more relaxed approach to the diet than is currently recommended. METHOD: We analysed associations between metabolic and cognitive measures in a mixed sample of English and Italian early-treated adults with PKU (N = 56). Metabolic measures were collected through childhood, adolescence and adulthood; cognitive measures were collected in adulthood. Metabolic measures included average Phe levels (average of median values for each year in a given period) and average Phe variations (average yearly standard deviations). Cognition was measured with IQ and a battery of cognitive tasks. RESULTS: Phe variation was as important, if not more important, than Phe average in predicting adult outcomes and contributed independently. Phe variation was particularly detrimental in childhood. Together, childhood Phe variation and adult Phe average predicted around 40% of the variation in cognitive scores. Poor cognitive scores (> 1 SD from controls) occurred almost exclusively in individuals with poor metabolic control and the risk of poor scores was about 30% higher in individuals with Phe values exceeding recommended thresholds. CONCLUSIONS: Our results provide support for current European guidelines (average Phe value = < 360 μmol/l in childhood; = < 600 μmo/l from 12 years onwards), but they suggest an additional recommendation to maintain stable levels (possibly Phe SD = < 180 μmol/l throughout life). PUBLIC SIGNIFICANCE STATEMENTS: We investigated the relationship between how well people with phenylketonuria control blood Phe throughout their life and their ability to carry out cognitive tasks in adulthood. We found that avoiding blood Phe peaks was as important if not more important that maintaining average low Phe levels. This was particularly essential in childhood. We also found that blood Phe levels above recommended European guidelines was associated with around 30% increase in the risk of poor cognitive outcomes

Assessment of computer-based training packages to improve the safety of older people’s driver behaviour

Examination of police records in Wales (STATS19 database) suggests older drivers are over represented in collisions turning across traffic and those involving failure to look properly, failure to judge the other vehicle or person’s path and performing a poor manoeuvre. A convened expert group suggests this is due to changes in attention, cognitive overload, processing speed, perceptual speed, working memory, task switching and eyesight associated with ageing. Training using computer-based packages can improve these cognitive and physiological issues associated with age. Performance on Useful Field of View (UFoV), Delayed Recall, Maze test and Dual N task computer tasks have all been shown to be related to number of crashes older drivers have. Of these only UFOV and Dual N task training improvements have been demonstrated to translate into improved driver behaviour, but overall more research is needed

Examining differences in neuropsychiatric symptom factor trajectories in empirically derived mild cognitive impairment subtypes

OBJECTIVE: The aim of this study was to examine neuropsychiatric symptom (NPS) factor severity progression over time in empirically derived (ED) mild cognitive impairment (MCI) subtypes. METHODS: Participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study diagnosed with MCI by ADNI protocol using conventional clinical (CC) criteria (n=788) were re-classified using cluster analysis as amnestic, dysnomic, dysexecutive MCI or cluster-derived normal (CC-Normal) using empirical criteria. Cognitively normal(CN) participants (n=207) were also identified. The Neuropsychiatric Inventory-Questionnaire (NPI-Q) was administered from baseline through 48-month follow-up. Exploratory factor analysis (EFA) was completed to determine the NPI-Q factor structure at 6-month follow-up. Multilevel modeling was used to determine NPI-Q symptom severity factor and apathy symptom progression over time by cognitive subtype. RESULTS: The EFA revealed that the NPI-Q consisted of two factors: hyperactivity/agitation and mood symptoms. Using clinical and empirical criteria, all MCI groups were identified as having more severe hyperactivity/agitation symptoms than CN participants. However, only the amnestic MCI group identified using empirical criteria showed an increase in symptom severity over time relative to CN participants. Mood factor and apathy symptoms were found to be more severe in dysexecutive and amnestic groups in both models. Similarly, both models identified a significant worsening of mood and apathy symptoms over time for dysexecutive and amnestic groups relative to CN participants. CONCLUSIONS: This study provides further support that empirical criteria aids in examining the progression of clinical characteristics associated with MCI. Further, it helps to identify which MCI subtypes may be at higher risk for NPS progression

Genome mining for screening and characterization of new lipopeptides with biocontrol applications

International audienceCyclic lipopeptides (CLiPs) are secondary metabolites produced by a variety of bacteria. They are nonribosomally synthesized thanks to huge enzymatic complexes working as assembly lines so-called NonRibosomal Peptide Synthetases (NRPS). The mode of synthesis leads to a structural biodiversity as they can contain nonproteinogenic aminoacids as well as D-isomers in the peptidyl moiety. On the other hand, some of them are produced as mixtures of isoforms displaying variable fatty acid chain lengths. For a few decades, CLiPs, especially those produced by PGPR (as Pseudomonas, Bacillus and Burkholderia) have been shown to play key roles in plant protection. Indeed, they can display direct antifungal activities or induce systemic resistance. In this way, CLiP producing microorganisms represent an untapped resource that can be mined for new biocontrol agents identification.Regarding the modular organisation of the NRPS together with structural features of the CLiPs, specific bioinformatics tools were developed with the aim i) to predict putative production of such compounds from genomic sequencing data, ii) to help in structure characterization by mass spectrometry and iii) to allow dereplication. These tools were used in the framework of the Bioscreen project of INTERREG FWVL SmartBioControl portefolio. Some successful examples will be presented