Cleveland Clinic researchers have leveraged AI to identify potential genetic risk factors and repurpose existing FDA-approved drugs for treating Parkinson’s disease. Their systems biology approach integrates various datasets to unveil hidden patterns and connections, paving the way for expedited therapeutic solutions.
Researchers at the Cleveland Clinic Genome Center have harnessed advanced artificial intelligence (AI) to probe into Parkinson’s disease, uncovering genetic risk factors and potential drug repurposing avenues. They utilized a systems biology approach, merging diverse data from genetics, proteomics, and patient records to reveal interconnected patterns that might remain hidden in solitary analyses.
Lead researcher Dr. Feixiong Cheng emphasizes the urgent need for targeted therapies against Parkinson’s, as the second most prevalent neurodegenerative disorder. Current treatments are limited to managing symptoms rather than altering disease progression, fueling a desperate push for groundbreaking disease-modifying options.
The complexity of Parkinson’s genetics presents challenges, as many mutations reside in non-coding regions of DNA rather than within active genes themselves. This necessitates identifying which underlying genes are impacted by these non-coding variants, leading to the team’s innovative approach utilizing integrative AI models.
By correlating known genetic variants with brain-specific databases, the researchers pinpointed how non-coding variations might influence gene activity in brain tissue. Their investigations identified several potential risk genes, including SNCA and LRRK2, both known to contribute to inflammation within the brain.
Once potential risk genes were identified, the team explored existing FDA-approved medications that could serve as potential treatments. They noted the burden of lengthy drug approval processes and the necessity of quicker therapeutic solutions for current Parkinson’s patients, illustrating the dire context of their research.
Integrating pharmacological data, the researchers discovered multiple candidate drugs that could be repurposed. Notably, they observed that patients prescribed the cholesterol medication simvastatin exhibited a reduced likelihood of Parkinson’s diagnoses, prompting further investigation into its therapeutic potential.
The next phase of research involves laboratory testing of simvastatin alongside various immunosuppressive and anti-anxiety drugs. Dr. Dou highlights the efficiency gained through network-based analyses, transforming a traditionally arduous process into a more streamlined approach for identifying promising therapeutic candidates.
This pioneering work received support from the National Institutes of Health, showcasing a concerted effort to combat the relentless advance of Parkinson’s disease through innovative research and thoughtful repurposing of existing medication.
Parkinson’s disease ranks as the second most common neurodegenerative disorder, trailing dementia. Despite its prevalence, therapeutic advancements have stagnated, primarily focusing on symptom management rather than curbing disease progression. This stark reality necessitates the innovative deployment of artificial intelligence and genetic research to unveil new treatments and identify risk factors that complicate the course of this grave condition.
The groundbreaking research by Cleveland Clinic scientists represents a beacon of hope in the fight against Parkinson’s disease, where AI is skillfully coupled with genetic analysis. By pinpointing risk genes and exploring existing medications, there’s potential not just for understanding the disease better, but also for fast-tracking therapeutic options for afflicted individuals. As the team moves forward with lab tests, the prospect of viable treatments grows brighter, offering a new narrative of possibility in Parkinson’s care.
Original Source: www.newswise.com
