Targeting Neuroinflammation in Parkinson’s Disease
Neuroinflammation plays a key role in the pathogenesis of Parkinson’s Disease (PD). Understanding biological targets associated with neuroinflammation in this disease may pave the way for effective treatments.
Neuroinflammation plays a key role in the pathogenesis of Parkinson’s Disease (PD). Understanding biological targets associated with neuroinflammation in this disease may pave the way for effective treatments. Using Causaly, we explored the potential of miR-195 as a target of neuroinflammation in PD.
Introduction to Parkinson’s Disease (PD)
Parkinson’s Disease (PD) is a neurodegenerative disease, affecting over 10 million people worldwide.¹ Characterized by the loss of dopamine-producing neurons in the brain, PD primarily affects movement, causing symptoms including tremors, rigidity and imbalance. Additionally, PD is often accompanied by depression and sleep disturbances. While treatments can provide relief and improve quality of life, they do not stop the progression of the disease.
The Role of Neuroinflammation
A key process in the pathogenesis of PD is neuroinflammation. When neurons become damaged, immune cells (including microglia and astrocytes) are activated in the brain. Initially, neuroinflammation aids in removing harmful or dysfunctional proteins. However, if this inflammatory response becomes chronic or excessive, this can cause further neuronal damage.
To understand how PD progresses and to develop effective treatments, it is important to understand the genes and proteins related to neuroinflammation. Here, we have utilized Causaly to identify and prioritize targets associated with neuroinflammation in PD.
Identifying Neuroinflammation Targets in PD
By machine-reading the literature, Causaly identified over 3000 potential targets for PD supported by almost 20,000 documents. Almost 600 of the targets of these are associated with neuroinflammation in PD, around two thirds of which have been studied in preclinical models, Figure 1. Here, targets were prioritized targets based on the most evidence (SNCA) and the linguistic strength of the presented evidence (miR-195).
Causaly vs. PubMed
The traditional method to identify relevant documents within biomedical literature involves searching for keywords using tools, such as PubMed. Performing the same search in PubMed by inputting keywords “targets”, “Parkinson’s Disease” “neuroinflammation” and “preclinical” returned 141 results across 15 pages.
Facing this data overload, users are confronted with the arduous task of navigating through an immense volume of information. This process could take days or weeks of reading time, which is highly impractical and subject to selection bias, with most scientists reading only the first few pages. In contrast, Causaly extracted relevant insights from 650+ documents, enabling the user to quickly discover relevant insights and explore all scientific evidence, significantly improving productivity.
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