Highlights d Mice with human tau and amyloid mutations develop progressive neuropathology d We identify transcriptional changes associated with tau and amyloid pathology d Discrete co-expression networks are associated with the progression of tau pathology d These are enriched for genes and pathways implicated in the onset of human AD

Cognitive impairment is a debilitating symptom in Parkinson’s disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson’s Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.

Alzheimer’s disease (AD)-associated synaptic dysfunction drives the progression of pathology from its earliest stages. Amyloid β (Aβ) species, both soluble and in plaque deposits, have been causally related to the progressive, structural and functional impairments observed in AD. It is, however, still unclear how Aβ plaques develop over time and how they progressively affect local synapse density and turnover. Here we observed, in a mouse model of AD, that Aβ plaques grow faster in the earlier stages of the disease and if their initial area is >500 µm2; this may be due to deposition occurring in the outer regions of the plaque, the plaque cloud. In addition, synaptic turnover is higher in the presence of amyloid pathology and this is paralleled by a reduction in pre- but not post-synaptic densities. Plaque proximity does not appear to have an impact on synaptic dynamics. These observations indicate an imbalance in the response of the pre- and post-synaptic terminals and that therapeutics, alongside targeting the underlying pathology, need to address changes in synapse dynamics.

Alzheimer's disease (AD)-associated synaptic dysfunction drives the progression of pathology from its earliest stages. Aβ species, both soluble and in plaque deposits, have been causally related to the progressive, structural and functional impairments observed in AD. It is, however, still unclear how Aβ plaques develop over time and how they progressively affect local synapse density and turnover. Here we observed, in a mouse model of AD, that Aβ plaques grow faster in the earlier stages of the disease and if their initial area is > 500 µm 2 ; this may be due to deposition occurring in the diffuse part of the plaque. In addition, synaptic turnover is higher in the presence of amyloid pathology and this is paralleled by a reduction in pre-but not post-synaptic densities. Plaque proximity does not appear to have an impact on synaptic dynamics. These observations indicate an imbalance in the response of the pre-and post-synaptic terminals and that therapeutics, alongside targeting the underlying pathology, need to address changes in synapse dynamics. KeywordsAlzheimer's disease, amyloid plaque, synapse, in vivo two-photon imaging, dendritic spine, axonal bouton DeclarationsCompeting interests -This work was conducted at Eli Lilly's research laboratories and several authors are employees of Eli Lilly.

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