Context dependent neuroprotective properties of prion protein (PrP)

Although it has been known for more than twenty years that an aberrant conformation of the prion protein (PrP) is the causative agent in prion diseases, the role of PrP in normal biology is undetermined. Numerous studies have suggested a protective function for PrP, including protection from ischemic and excitotoxic lesions and several apoptotic insults. On the other hand, many observations have suggested the contrary, linking changes in PrP localization or domain structure—independent of infectious prion conformation—to severe neuronal damage. Surprisingly, a recent report suggests that PrP is a receptor for toxic oligomeric species of a-β, a pathogenic fragment of the amyloid precursor protein, and likely contributes to disease pathogenesis of Alzheimer disease. We sought to access the role of PrP in diverse neurological disorders. First, we confirmed that PrP confers protection against ischemic damage using an acute stroke model, a well characterized association. After ischemic insult, PrP knockouts had dramatically increased infarct volumes and decreased behavioral performance compared to controls. To examine the potential of PrP''s neuroprotective or neurotoxic properties in the context of other pathologies, we deleted PrP from several transgenic models of neurodegenerative disease. Deletion of PrP did not substantially alter the disease phenotypes of mouse models of Parkinson disease or tauopathy. Deletion of PrP in one of two Huntington disease models tested, R6/2, modestly slowed motor deterioration as measured on an accelerating rotarod but otherwise did not alter other major features of the disease. Finally, transgenic overexpression of PrP did not exacerbate the Huntington motor phenotype. These results suggest that PrP has a context-dependent neuroprotective function and does not broadly contribute to the disease models tested herein.Key words: neurodegeneration, protein misfolding, PrP, home cage, stroke     

Effective degree network disease models

An effective degree approach to modeling the spread of infectious diseases on a network is introduced and applied to a disease that confers no immunity (a Susceptible-Infectious-Susceptible model, abbreviated as SIS) and to a disease that confers permanent immunity (a Susceptible-Infectious-Recovered model, abbreviated as SIR). Each model is formulated as a large system of ordinary differential equations that keeps track of the number of susceptible and infectious neighbors of an individual. From numerical simulations, these effective degree models are found to be in excellent agreement with the corresponding stochastic processes of the network on a random graph, in that they capture the initial exponential growth rates, the endemic equilibrium of an invading disease for the SIS model, and the epidemic peak for the SIR model. For each of these effective degree models, a formula for the disease threshold condition is derived. The threshold parameter for the SIS model is shown to be larger than that derived from percolation theory for a model with the same disease and network parameters, and consequently a disease may be able to invade with lower transmission than predicted by percolation theory. For the SIR model, the threshold condition is equal to that predicted by percolation theory. Thus unlike the classical homogeneous mixing disease models, the SIS and SIR effective degree models have different disease threshold conditions.     

Validation of the IHE Cohort Model of Type 2 Diabetes and the Impact of Choice of Macrovascular Risk Equations

Background

Health-economic models of diabetes are complex since the disease is chronic, progressive and there are many diabetic complications. External validation of these models helps building trust and satisfies demands from decision makers. We evaluated the external validity of the IHE Cohort Model of Type 2 Diabetes; the impact of using alternative macrovascular risk equations; and compared the results to those from microsimulation models.

Methods

The external validity of the model was analysed from 12 clinical trials and observational studies by comparing 167 predicted microvascular, macrovascular and mortality outcomes to the observed study outcomes. Concordance was examined using visual inspection of scatterplots and regression-based analysis, where an intercept of 0 and a slope of 1 indicate perfect concordance. Additional subgroup analyses were conducted on ‘dependent’ vs. ‘independent’ endpoints and microvascular vs. macrovascular vs. mortality endpoints.

Results

Visual inspection indicates that the model predicts outcomes well. The UKPDS-OM1 equations showed almost perfect concordance with observed values (slope 0.996), whereas Swedish NDR (0.952) and UKPDS-OM2 (0.899) had a slight tendency to underestimate. The R ² values were uniformly high (>0.96). There were no major differences between ‘dependent’ and ‘independent’ outcomes, nor for microvascular and mortality outcomes. Macrovascular outcomes tended to be underestimated, most so for UKPDS-OM2 and least so for NDR risk equations.

Conclusions

External validation indicates that the IHE Cohort Model of Type 2 Diabetes has predictive accuracy in line with microsimulation models, indicating that the trade-off in accuracy using cohort simulation might not be that large. While the choice of risk equations was seen to matter, each were associated with generally reasonable results, indicating that the choice must reflect the specifics of the application. The largest variation was observed for macrovascular outcomes. There, NDR performed best for relatively recent and well-treated patients, while UKPDS-OM1 performed best for the older UKPDS cohort.     

Acyl-CoA thioesterases belong to a novel gene family of peroxisome proliferator-regulated enzymes involved in lipid metabolism

Acyl-CoA thioesterases hydrolyze acyl-CoAs to the corresponding free fatty acid plus coenzyme A. The activity is strongly induced in rat and mouse liver after feeding the animals peroxisome proliferators (PPs). To elucidate the role of these enzymes in lipid metabolism, the authors have cloned the cDNAs corresponding to the inducible cytosolic and mitochondrial type I enzymes (CTE-I and MTE-I), and studied tissue expression and nutritional regulation of expression of the mRNAs in mice. The constitutive expression of both mRNAs was low in liver, with CTE-I expressed mainly in kidney and brown adipose tissue, and MTE-I expressed in brown adipose tissue and heart. As expected, the expression in liver of both the CTE-I and MTE-I mRNAs were strongly induced (>50-fold) by treatment with clofibrate. A similar level of induction was observed by fasting and a time-course study showed that the CTE-I and MTE-I mRNAs were increased already at 6 h after removal of the diet. Refeeding normal chow diet to mice fasted for 24h normalized the mRNA levels with a T _1/2 of about 3–4 h. Feeding mice a fat-free diet further decreased the expression, possibly indicating repression of expression. The strong expression of MTE-I and CTE-I in the heart was increased about 10-fold by fasting. To further characterize these highly regulated enzymes, the authors have cloned the corresponding genes and promoter regions. The structures of the two genes were found to be very similar, consisting of three exons and two introns. Exon-intron borders conform to general consensus sequences, and, especially, the first exon appears to be highly conserved. The promoter regions of both the CTE-I and MTE-I genes contain putative PP response elements, suggesting an involvement of PP-activated receptors in the regulation of these genes.     

Binding of human milk to pathogen receptor DC-SIGN varies with bile salt-stimulated lipase (BSSL) gene polymorphism

Objective

Dendritic cells bind an array of antigens and DC-SIGN has been postulated to act as a receptor for mucosal pathogen transmission. Bile salt-stimulated lipase (BSSL) from human milk potently binds DC-SIGN and blocks DC-SIGN mediated trans-infection of CD4⁺ T-lymphocytes with HIV-1. Objective was to study variation in DC-SIGN binding properties and the relation between DC-SIGN binding capacity of milk and BSSL gene polymorphisms.

Study Design

ELISA and PCR were used to study DC-SIGN binding properties and BSSL exon 11 size variation for human milk derived from 269 different mothers distributed over 4 geographical regions.

Results

DC-SIGN binding properties were highly variable for milks derived from different mothers and between samplings from different geographical regions. Differences in DC-SIGN binding were correlated with a genetic polymorphism in BSSL which is related to the number of 11 amino acid repeats at the C-terminus of the protein.

Conclusion

The observed variation in DC-SIGN binding properties among milk samples may have implications for the risk of mucosal transmission of pathogens during breastfeeding.