CSF1R inhibitor JNJ-40346527 attenuates microglial proliferation and neurodegeneration in P301S mice

Neuroinflammation and microglial activation are significant processes in Alzheimer’s disease pathology. Recent genome-wide association studies have highlighted multiple immune-related genes in association with Alzheimer’s disease, and experimental data have demonstrated microglial proliferation as a significant component of the neuropathology. In this study, we tested the efficacy of the selective CSF1R inhibitor JNJ-40346527 (JNJ-527) in the P301S mouse tauopathy model. We first demonstrated the anti-proliferative effects of JNJ-527 on microglia in the ME7 prion model, and its impact on the inflammatory profile, and provided potential CNS biomarkers for clinical investigation with the compound, including pharmacokinetic/pharmacodynamics and efficacy assessment by TSPO autoradiography and CSF proteomics. Then, we showed for the first time that blockade of microglial proliferation and modification of microglial phenotype leads to an attenuation of tau-induced neurodegeneration and results in functional improvement in P301S mice. Overall, this work strongly supports the potential for inhibition of CSF1R as a target for the treatment of Alzheimer’s disease and other tau-mediated neurodegenerative diseases

MRI data-driven algorithm for the diagnosis of behavioural variant frontotemporal dementia

Introduction: Structural brain imaging is paramount for the diagnosis of behavioural variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis. Methods: A total of 515 subjects from two different bvFTD cohorts (training and independent validation cohorts) were used to perform voxel-wise morphometric analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from deformation-based morphometry differences in isolation and together with semantic fluency. Tenfold cross validation was used to assess the performance of the classifier within the training cohort. A second held-out cohort of genetically confirmed bvFTD cases was used for additional validation. Results: Average 10-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In the separate validation cohort of definite bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added semantic fluency scores. Conclusion: Our results show that structural MRI and semantic fluency can accurately predict bvFTD at the individual subject level within a completely independent validation cohort coming from a different and independent database

Use of Antibiotic Resistance Analysis for Representativeness Testing of Multiwatershed Libraries

The use of antibiotic resistance analysis (ARA) for microbial source tracking requires the generation of a library of isolates collected from known sources in the watershed. The size and composition of the library are critical in determining if it represents the diversity of patterns found in the watershed. This study was performed to determine the size that an ARA library needs to be to be representative of the watersheds for which it will be used and to determine if libraries from different watersheds can be merged to create multiwatershed libraries. Fecal samples from known human, domesticated, and wild animal sources were collected from six Virginia watersheds. From these samples, enterococci were isolated and tested by ARA. Based on cross-validation discriminant analysis, only the largest of the libraries (2,931 isolates) were found to be able to classify nonlibrary isolates as well as library isolates (i.e., were representative). Small libraries tended to have higher average rates of correct classification, but were much less able to correctly classify nonlibrary isolates. A merged multiwatershed library (6,587 isolates) was created and was found to be large enough to be representative of the isolates from the contributing watersheds. When isolates that were collected from the contributing watersheds approximately 1 year later were analyzed with the multiwatershed library, they were classified as well as the isolates in the library, suggesting that the resistance patterns are temporally stable for at least 1 year. The ability to obtain a representative, temporally stable library demonstrates that ARA can be used to identify sources of fecal pollution in natural waters