Age is the major risk factor for Alzheimer´s disease (AD), and as the world’s population is becoming older it is
increasingly prevalent. There are many commonalities between aging and AD, both on the molecular and
systems level. There is also ample evidence, in particular from work in animal models, that a broad spectrum of
aging-preventive interventions that confer longevity have the ability to alleviate diverse aspects of AD pathology,
such as Aß and tau aggregation. These pathologies lead to severe neurodegeneration and occurrence of clinical
symptoms such as memory loss, mood swings and changes in personality. No disease-modifying treatments
exist, only medications that relieve the symptoms temporarily. To find treatments that prevent disease
progression, testing drugs that have already been approved for other indications – a strategy referred to as drug
repurposing – may be useful. A major benefit of drug repurposing is that it speeds up drug development and
reduces the risks for patients, since these drugs have already passed safety assessment in humans.
Thus, we propose a data-driven approach to search among drugs used for other age-related conditions and
identify some that can be repurposed for the prevention of AD.
Towards this approach, we will investigate the effect of the 20 most commonly used drug classes among 65+
year-olds in Sweden (>200 substances also approved for use in the U.S.) on biological aging and AD in a series
of epidemiological analyses. We will use deeply phenotyped longitudinal cohort data to see how drug treatment
changes biological aging trajectories, as well as apply Mendelian Randomizations to mimic the modulation on
drug targets using large-scale genotyping data and emulated target trials in the Swedish Prescribed Drug
Register linked to a quality register on dementia. Following this, the individual substances within the 2-3 most
promising drug classes will be screened in vitro in human cellular models of AD and in vivo in C. elegans models
of aging and of human Aß and tau aggregation and toxicity. Top candidates will be tested in established and
most relevant AD mouse models and in models of accelerated aging.
Taken together, our approach to discover new drugs for AD prevention by screening already approved
substances bears great benefits. The fact that much of the testing happens in silico and that the screening
focuses only on drugs that are already approved for use in patients makes our approach faster and more cost-
effective than conventional de novo compound screens.