Modeling Alzheimer's disease in progeria mice. An age-related concept

More than a number: Incorporating the aged phenotype to improve in vitro and in vivo modeling of neurodegenerative disease

Age is the number one risk factor for developing a neurodegenerative disease (ND), such as Alzheimer's disease (AD) or Parkinson's disease (PD). With our rapidly ageing world population, there will be an increased burden of ND and need for disease-modifying treatments. Currently, however, translation of research from bench to bedside in NDs is poor. This may be due, at least in part, to the failure to account for the potential effect of ageing in preclinical modelling of NDs. While ageing can impact upon physiological response in multiple ways, only a limited number of preclinical studies of ND have incorporated ageing as a factor of interest. Here, we evaluate the aged phenotype and highlight the critical, but unmet, need to incorporate aspects of this phenotype into both the in vitro and in vivo models used in ND research. Given technological advances in the field over the past several years, we discuss how these could be harnessed to create novel models of ND that more readily incorporate aspects of the aged phenotype. This includes a recently described in vitro panel of ageing markers, which could help lead to more standardised models and improve reproducibility across studies. Importantly, we cannot assume that young cells or animals yield the same responses as seen in the context of ageing; thus, an improved understanding of the biology of ageing, and how to appropriately incorporate this into the modelling of ND, will ensure the best chance for successful translation of new therapies to the aged patient.

A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression

BACKGROUND

Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies.

METHODS

We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD-risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed.

RESULTS

Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD-risk SNPs were significant predictors of AD progression.

DISCUSSION

The model successfully estimated the contribution of AD-risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine.

Inhibition of activin A receptor signalling attenuates age-related pathological cardiac remodelling

In the heart, ageing is associated with DNA damage, oxidative stress, fibrosis and activation of the activin signalling pathway, leading to cardiac dysfunction. The cardiac effects of activin signalling blockade in progeria are unknown. This study investigated the cardiac effects of progeria induced by attenuated levels of Ercc1, which is required for DNA excision and repair, and the impact of activin signalling blockade using a soluble activin receptor type IIB (sActRIIB). DNA damage and oxidative stress were significantly increased in Ercc1^Δ/− hearts, but were reduced by sActRIIB treatment. sActRIIB treatment improved cardiac systolic function and induced cardiomyocyte hypertrophy in Ercc1^Δ/− hearts. RNA-sequencing analysis showed that in Ercc1^Δ/− hearts, there was an increase in pro-oxidant and a decrease in antioxidant gene expression, whereas sActRIIB treatment reversed this effect. Ercc1^Δ/− hearts also expressed higher levels of anti-hypertrophic genes and decreased levels of pro-hypertrophic ones, which were also reversed by sActRIIB treatment. These results show for the first time that inhibition of activin A receptor signalling attenuates cardiac dysfunction, pathological tissue remodelling and gene expression in Ercc1-deficient mice and presents a potentially novel therapeutic target for heart diseases.

Summary: Attenuated DNA repair is associated with pathological cardiac remodelling and gene expression. Much of this phenotype is attenuated by inhibition of the activin signalling pathway using soluble activin receptor treatment.