Alzheimer's disease is the most common dementia and affects around 35 million individuals worldwide. It is suggested that the accumulation of brain 'garbage' (like Abeta plaques and Tau tangles), due to compromised 'collection and recycling', is a cause of Alzheimer. This project aims to understand why the 'garbage truck' stops to work in Alzheimer's disease. Once we understand the reason, we could use the modern methods, including the cost-effective artificial intelligence, to design drug candidates against Alzheimer. The success of this project may have translational potential, and in a long run big socio-economic impact.
Alzheimer’s disease (AD), the most common form of dementia, affects over 35 million people worldwide and causes
formidable economic challenges. Since 2003, over 250 drug candidates, predominantly targeting two pathological
proteins: amyloid- (A) and Tau, have been tested in clinical trials for AD and have all failed. As such, there is a need to
pursue new mechanistic studies in order to better understand the underlying causes of AD, and to discover new and
effective drug targets. Mitochondria operate as cellular “powerhouses” and play a pivotal role in neuroplasticity and
memory. Mitochondria are constantly exposed to stress and damage; thus, dysfunctional mitochondria must be
efficiently eliminated via a cellular self-clearance system termed “mitophagy”.
The Evandro F. Fang group at UiO is among the first groups to propose and demonstrate a causative role for
defective mitophagy as a key driver in AD initiation and progression, and has demonstrated mitophagy induction as
an effective way to inhibit memory loss in multiple AD animal models. However, the intricate mechanisms underlying
the link between defective mitophagy in Tau pathology and how mitophagy induction inhibits the progression of p-
Tau and NFTs are largely unknown. Here, we aim to test the hypothesis that ‘Impaired mitophagy in the entorhinal
cortex (EC) contributes to initiation and progression of Tau pathology in AD’, and based on the new drug target
‘impaired mitophagy’ to identify potent neuronal mitophagy inducers for use as anti-AD drug candidates via an
artificial intelligence (AI)-based approach. Understanding the mechanisms underlying defective mitophagy and its
roles in AD may revolutionise our understanding of AD aetiology and propel clinical drug discovery in new and fruitful
directions.