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Harnessing Endophenotypes for Alzheimer’s Disease Drug Repurposing

Dr. Cheng’s team developed an endophenotype-based drug repurposing methodology that identified the FDA-approved drug sildenafil as a candidate for the prevention and treatment of Alzheimer’s disease.

12/06/2021




A new Cleveland Clinic-led study has identified sildenafil, an FDA-approved therapy for erectile dysfunction (Viagra) and pulmonary hypertension (Revatio), as a promising drug candidate to help prevent and treat Alzheimer’s disease (AD).

According to findings published in Nature Aging, the research team, led by Feixiong Cheng, PhD, Genomic Medicine Institute, developed an endophenotype-based drug repurposing methodology to screen and validate FDA-approved drugs as potential therapies for AD. They determined via analysis of large-scale patient data that sildenafil is associated with reduced AD incidence, indicating the need for rigorous clinical trial testing of sildenafil’s treatment efficacy in AD patients.

Endophenotypes reveal potential AD drug candidates

Without the development of effective disease-modifying treatments, AD is set to impact 13.8 million Americans by 2050, underscoring the need for rapid development of prevention and treatment strategies. Drug repurposing, or the use of an existing drug for new therapeutic purposes, offers a practical alternative to the costly and time-consuming traditional drug discovery process.

“This paper is an example of a growing area of research in precision medicine where big data is key to connecting the dots between existing drugs and a complex disease like Alzheimer’s,” said Jean Yuan, MD, PhD, Translational Bioinformatics and Drug Development program director at the National Institute on Aging (NIA), part of the National Institutes of Health (NIH), which funded this research. “This is one of many efforts we are supporting to find existing drugs or available safe compounds for other conditions that would be good candidates for Alzheimer’s disease clinical trials.”

Dr. Cheng’s team has found that understanding subtypes (endophenotypes) of neurodegenerative diseases such as AD may help to reveal common underlying mechanisms. Clearly defining endophenotypes could serve as a foundation for generating actionable targets for drug repurposing for subtypes of AD. Amyloidosis and tauopathy are responsible for the buildup of beta amyloid and tau proteins in the brain that lead to amyloid plaques and tau neurofibrillary tangles (two hallmark AD-related brain changes). The amount and location of these proteins in the brain may help define endophenotypes. However, no FDA-approved, small molecule anti-amyloid or anti-tau AD treatments currently exist, with hundreds of clinical trials for such treatments having failure in the past decade.

“Recent studies show that the interplay between amyloid and tau is a greater contributor to AD than either by itself,” said Dr. Cheng. “Therefore, we hypothesized that drugs targeting the molecular network intersection of amyloid and tau endophenotypes should have the greatest potential for success.”

Using the human interactome (the complex network of protein-protein interactions that influence cellular function and disease biology), the researchers mapped the interactions between genes/proteins involved in amyloidosis and tauopathy to build connected sub-networks mechanistically linked to the amyloid and tau endophenotypes that may be synergistic. They then measured proximity of the sub-networks (termed endophenotype modules) to drug targets of approximately 1,600 FDA-approved drugs, where closer proximity indicates a greater likelihood that a drug could be an effective AD treatment.

“We found that drugs targeting both amyloid and tau had significantly closer network proximity with the modules compared with those targeting just one or the other,” said Dr. Cheng. “Sildenafil, which has been shown to significantly improve cognition and memory in preclinical models, presented as the best drug candidate.”

Sildenafil use associated with decreased AD risk

Utilizing a database of more than 7 million patients, the researchers examined the relationship between sildenafil and AD outcomes by comparing sildenafil users to non-users, which included patients using comparator drugs that either were in an active AD clinical trial (losartan or metformin) or were not yet reported as relevant to AD (diltiazem or glimepiride).

They found that sildenafil users were 69% less likely to develop AD than non-sildenafil users. Specifically, sildenafil had a 55% reduced risk of AD compared to losartan, 63% compared to metformin, 65% compared to diltiazem and 64% compared to glimepiride.

“Notably, we found that sildenafil use reduced the likelihood of AD in individuals with coronary artery disease, hypertension and type 2 diabetes, all of which are comorbidities significantly associated with risk of AD, as well as in those without,” added Dr. Cheng.  

To further explore sildenafil’s effect on AD, the researchers developed an AD patient-derived neuron model using pluripotent stem cells. In the model, they found that sildenafil increased neurite growth and decreased the hyperphosphorylation of tau (which leads to neurofibrillary tangles), offering biological insights into how sildenafil may influence disease-related brain changes.

Next steps

“Because our findings only establish an association between sildenafil use and reduced AD incidence, we are now planning a mechanistic trial and a phase II randomized clinical trial to test causality and confirm sildenafil’s clinical benefits for AD patients,” said Dr. Cheng. “We also foresee our approach being applied to other neurodegenerative diseases, including Parkinson’s disease and amyotrophic lateral sclerosis, to accelerate the drug discovery process.”

Dr. Cheng’s team is currently applying cutting-edge artificial intelligence and network medicine technologies to identify novel targets and repurposable medicines for AD treatment using human genome sequencing data from the Alzheimer's Disease Sequencing Project, a large NIA-funded consortium that aims to identify the genetic underpinnings of AD. For example, they are investigating other types of endophenotypes including inflammatory endophenotypes, and are utilizing a combination therapy design approach to identify effective drug combinations for AD by assembling multiple endophenotype-based findings.

Jiansong Fang, PhD, a former research scholar in Dr. Cheng’s lab; Pengyue Zhang, PhD, an assistant research professor at Indiana University School of Medicine; Yadi Zhou, PhD, a data scientist in Dr. Cheng’s lab; and Chien-Wei Chiang, PhD, a research scientist at The Ohio State University College of Medicine, are co-first authors on the study. Dr. Cheng presented the initial findings at the 2021 Alzheimer’s Association International Conference in July. The study was supported by NIA, NIH grants R01AG066707 and R01AG066707-01S1, and the Translational Therapeutics Core of the Cleveland Alzheimer's Disease Research Center.




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