Citalopram reduces aggregation of ATXN3 in a YAC transgenic mouse model of Machado-Joseph disease

Machado-Joseph disease, also known as spinocerebellar ataxia type 3, is a fatal polyglutamine disease with no disease-modifying treatment. The selective serotonin reuptake inhibitor citalopram was shown in nematode and mouse models to be a compelling repurposing candidate for Machado-Joseph disease therapeutics. We sought to confirm the efficacy of citalopram to decrease ATXN3 aggregation in an unrelated mouse model of Machado-Joseph disease. Four-week-old YACMJD84.2 mice and non-transgenic littermates were given citalopram 8 mg/kg in drinking water or water for 10 weeks. At the end of treatment, brains were collected for biochemical and pathological analyses. Brains of citalopram-treated YACMJD84.2 mice showed an approximate 50% decrease in the percentage of cells containing ATXN3-positive inclusions in the substantia nigra and three examined brainstem nuclei compared to controls. No differences in ATXN3 inclusion load were observed in deep cerebellar nuclei of mice. Citalopram effect on ATXN3 aggregate burden was corroborated by immunoblotting analysis. While lysates from the brainstem and cervical spinal cord of citalopram-treated mice showed a decrease in all soluble forms of ATXN3 and a trend toward reduction of insoluble ATXN3, no differences in ATXN3 levels were found between cerebella of citalopram-treated and vehicle-treated mice. Citalopram treatment altered levels of select components of the cellular protein homeostatic machinery that may be expected to enhance the capacity to refold and/or degrade mutant ATXN3. The results here obtained in a second independent mouse model of Machado-Joseph disease further support citalopram as a potential drug to be repurposed for this fatal disorder.This work was funded by Becky Babcox Research Fund/pilot research award G015617, University of Michigan to M.C.C. and NINDS/NIH R01NS038712 to H.L.P. The work performed at the University of Minho was funded by the European Regional Development Funds (FEDER), through the Competitiveness Factors Operational Programme (COMPETE), and by National funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER-007038. This article was developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Program (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the FEDER. This work was also supported by FCT and COMPETE through the projects [PTDC/SAU-GMG/112617/2009] (to P.M.) and [EXPL/BIM-MEC/ 0239/2012] (to A.T.C.); by FCT through the project [POCI-01-0145- FEDER-016818 (PTDC/NEU-NMC/3648/2014)] (to P.M.); by National Ataxia Foundation (to P.M. and to A.T.C.); and by Ataxia UK (to P.M.). S.D.S. and A.T.C. were supported by fellowships from FCT, SFRH/BD/ 78388/2011 and SFRH/BPD/102317/2014, respectively. FCT fellowships are co-financed by POPH, QREN, Governo da República Portuguesa and EU/FSE

Identifying Consensus Disease Pathways in Parkinson's Disease Using an Integrative Systems Biology Approach

Parkinson's disease (PD) has had six genome-wide association studies (GWAS) conducted as well as several gene expression studies. However, only variants in MAPT and SNCA have been consistently replicated. To improve the utility of these approaches, we applied pathway analyses integrating both GWAS and gene expression. The top 5000 SNPs (p<0.01) from a joint analysis of three existing PD GWAS were identified and each assigned to a gene. For gene expression, rather than the traditional comparison of one anatomical region between sets of patients and controls, we identified differentially expressed genes between adjacent Braak regions in each individual and adjusted using average control expression profiles. Over-represented pathways were calculated using a hyper-geometric statistical comparison. An integrated, systems meta-analysis of the over-represented pathways combined the expression and GWAS results using a Fisher's combined probability test. Four of the top seven pathways from each approach were identical. The top three pathways in the meta-analysis, with their corrected p-values, were axonal guidance (p = 2.8E-07), focal adhesion (p = 7.7E-06) and calcium signaling (p = 2.9E-05). These results support that a systems biology (pathway) approach will provide additional insight into the genetic etiology of PD and that these pathways have both biological and statistical support to be important in PD

Evolution and Origin of PVY

International audienceThe mechanisms by which Potato virus Y variants are generated and selected are still unclear. Spontaneous mutations generated by uncorrected replication error and recombination events between viral isolates during co-infection of plant cells are the main likely source of genetic diversity. This high level of diversity generation is essential for virus evolution and survival in different environments. Different PVY strain groups have appeared over time: firstly, non-recombinant PVYC, PVYO and PVYN strains and, more recently, recombinant PVYN-Wi and PVYNTN strains with novel biological characteristics and the ability to cause potato tuber necrotic ringspot disease (PTNRD). Increased fitness of the recombinant strains appears to have enabled them to replace the non-recombinant variants in most potato growing areas of the world. Partial sequencing of PVY genome (P1, HC-Pro, CP, recombinant junctions) and whole genome sequencing has shown that non-recombinant and recombinant variants are present in potatoes and other plant hosts. Phylogenetic analyses have been applied to document changes in viral isolates and to establish the relationships between different viral isolates. Traditional phylogenetic analysis was, however, developed for bifurcating phylogenies and not for analysing recombination, as a result of which this presents challenges to these analyses which will be outlined in this chapter. The ongoing worldwide studies on PVY characterisation suggest that new variants with distinct biological properties are likely to be uncovered in the future. Emerging technologies such as next generation sequencing will provide valuable insights into PVY population dynamics and evolution in future