Assessment of the quality of brain regions and neuroimaging metrics as biomarkers of Alzheimer’s disease

Alzheimer Disease (AD) is characterized by progressive cognitive decline and dementia. Earlier diagnosis and classification of different stages of the disease are currently the main challenges and can be assessed by neuroimaging. With this work we aim to evaluate the quality of brain regions and neuroimaging metrics as biomarkers of AD. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox functionalities were used to study AD by T1weighted, Diffusion Tensor Imaging and 18FAV45 PET, with data obtained from the AD Neuroimaging Initiative database, specifically 12 healthy controls (CTRL) and 33 patients with early mild cognitive impairment (EMCI), late MCI (LMCI) and AD (11 patients/group). The metrics evaluated were gray-matter volume (GMV), cortical thickness (CThk), mean diffusivity (MD), fractional anisotropy (FA), fiber count (FiberConn), node degree (Deg), cluster coefficient (ClusC) and relative standard-uptake-values (rSUV). Receiver Operating Characteristic (ROC) curves were used to evaluate and compare the diagnostic accuracy of the most significant metrics and brain regions and expressed as area under the curve (AUC). Comparisons were performed between groups. The RH-Accumbens/Deg demonstrated the highest AUC when differentiating between CTRLEMCI (82%), whether rSUV presented it in several brain regions when distinguishing CTRL-LMCI (99%). Regarding CTRL-AD, highest AUC were found with LH-STG/FiberConn and RH-FP/FiberConn (~100%). A larger number of neuroimaging metrics related with cortical atrophy with AUC>70% was found in CTRL-AD in both hemispheres, while in earlier stages, cortical metrics showed in more confined areas of the temporal region and mainly in LH, indicating an increasing of the spread of cortical atrophy that is characteristic of disease progression. In CTRL-EMCI several brain regions and neuroimaging metrics presented AUC>70% with a worst result in later stages suggesting these indicators as biomarkers for an earlier stage of MCI, although further research is necessary.

Relationship of PON1 192 and 55 gene polymorphisms to calcific valvular aortic stenosis

Introduction and Objectives - Paraoxonases may exert anti-atherogenic action by reducing lipid peroxidation. Previous studies examined associations between polymorphisms in the paraoxonase 1 (PON1) gene and development of coronary artery disease (CAD), with inconsistent results. Given the similarities in clinical and pathophysiological risk factors of CAD and calcific aortic valve stenosis (CAVS), we postulated a link between PON1 alleles and CAVS progression. Methods - We investigated the association between PON1 55 and 192 single nucleotide polymorphisms (SNPs), their enzyme activity, and CAVS progression assessed by aortic valve area and transvalvular peak velocity in 67 consecutive patients with moderate CAVS and 251 healthy controls. Results - PON1 paraoxonase activity was higher in CAVS patients (P<0.001). The PON1 genotype Q192R SNP (P=0.03) and variant allele (R192) (P=0.01) frequencies differed between CAVS patients and controls. Significant association existed between PON1 enzyme activity, phenotypic effects of PON1 192 genotype polymorphisms, and CAVS progression, but not between PON1 55 and high-density lipoprotein (P=0.44) or low-density lipoprotein cholesterol (P=0.12), between 192 genotype and high-density lipoprotein (P=0.24) or low-density lipoprotein cholesterol (P=0.52). Conclusion - The PON1 genotype Q192R SNP has an important effect on CAVS disease progression. This study helps outline a genotype-phenotype relationship for PON1 in this unique population.

Synthesis and characterization of rabies virus glycoprotein-tagged amphiphilic cyclodextrins for siRNA delivery in human glioblastoma cells: in vitro analysis

In man brain cancer is an aggressive, malignant form of tumour, it is highly infiltrative in nature, is associated with cellular heterogeneity and affects cerebral hemispheres of the brain. Current drug therapies are inadequate and an unmet clinical need exists to develop new improved therapeutics. The ability to silence genes associated with disease progression by using short interfering RNA (siRNA) presents the potential to develop safe and effective therapies. In this work, in order to protect the siRNA from degradation, promote cell specific uptake and enhance gene silencing efficiency, a PEGylated cyclodextrin (CD)-based nanoparticle, tagged with a CNS-targeting peptide derived from the rabies virus glycoprotein (RVG) was formulated and characterized. The modified cyclodextrin derivatives were synthesized and co-formulated to form nanoparticles containing siRNA which were analysed for size, surface charge, stability, cellular uptake and gene-knockdown in brain cancer cells. The results identified an optimised co-formulation prototype at a molar ratio of 1:1.5:0.5 (cationic cyclodextrin:PEGylated cyclodextrin:RVG-tagged PEGylated cyclodextrin) with a size of 281±39.72nm, a surface charge of 26.73±3mV, with efficient cellular uptake and a 27% gene-knockdown ability. This CD-based formulation represents a potential nanocomplex for systemic delivery of siRNA targeting brain cancer.