Reprogramming neurodegeneration in the big data era

Multi-Layer Picture of Neurodegenerative Diseases: Lessons from the Use of Big Data through Artificial Intelligence

In the big data era, artificial intelligence techniques have been applied to tackle traditional issues in the study of neurodegenerative diseases. Despite the progress made in understanding the complex (epi)genetics signatures underlying neurodegenerative disorders, performing early diagnosis and developing drug repurposing strategies remain serious challenges for such conditions. In this context, the integration of multi-omics, neuroimaging, and electronic health records data can be exploited using deep learning methods to provide the most accurate representation of patients possible. Deep learning allows researchers to find multi-modal biomarkers to develop more effective and personalized treatments, early diagnosis tools, as well as useful information for drug discovering and repurposing in neurodegenerative pathologies. In this review, we will describe how relevant studies have been able to demonstrate the potential of deep learning to enhance the knowledge of neurodegenerative disorders such as Alzheimer's and Parkinson's diseases through the integration of all sources of biomedical data.

The Rat Prefrontal-Cortex Transcriptome: Effects of Aging and Sporadic Alzheimer's Disease-Like Pathology

Alzheimer's disease (AD) is the most widespread late-life dementia and involves the prefrontal cortex, a vulnerable brain region implicated in memory, emotion, cognition, and decision-making behavior. To understand the molecular differences between the effects of aging and AD on the prefrontal cortex, this study characterized the age-dependent changes in gene expression in Wistar rats (control) and OXYS rats (rodents that simulate key characteristics of sporadic AD) using RNA sequencing. We found that major altered biological processes during aging in Wistar rats were associated with immune processes. Gene expression changes during development of AD-like pathology as well as at the preclinical stage were related to neuronal plasticity, catalytic activity, lipid and immune processes, and mitochondria. A comparison of genes between data sets "OXYS rats" and "human AD" revealed similarity in expression alterations of genes related primarily to mitochondrial function; immune, endocrine, and circulatory systems; signal transduction; neuronal and synaptic processes; hypoxia; and apoptosis. Expression changes in mitochondrial processes identified in OXYS rats by RNA sequencing were confirmed by ultrastructural neuronal organelle alterations and low activity of respiratory chain complexes I, IV, and V in cortical mitochondria, suggesting that mitochondrial dysfunction appears to mediate or possibly even initiate the development of AD.

Societal Burden and Persisting Unmet Needs of Parkinson’s Disease

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