Antibody Therapy Slows Symptoms in Rapidly Progressing Parkinson’s Disease

Post by Baldomero B. Ramirez Cantu

The takeaway

Treatment with the monoclonal antibody Prasinezumab slows the progression of motor deficits in individuals with Parkinson's disease, particularly in subpopulations characterized by rapid progression.

What's the science?

Parkinson's disease (PD) is a progressive neurological disorder characterized by tremors, stiffness, and impaired movement due to the loss of dopamine-producing neurons in the brain. Monoclonal antibody treatments involve the use of antibodies that target specific proteins implicated in disease processes, promoting clearance of pathological agents, and offering a promising avenue for targeted therapeutic intervention. Recently, the use of monoclonal antibody therapy has shown promise for the treatment of Alzheimer’s disease, however, these treatments remained relatively unexplored for Parkinson's disease. This week in Nature Medicine, Gennaro Pagano and colleagues published an article exploring the impact of the monoclonal antibody Prasinezumab on the progression of motor symptoms in PD.

How did they do it?

Researchers analyzed data collected during the Trial of Prasinezumab in Early-Stage Parkinson’s Disease or PASADENA study, which involved screening 443 individuals, with 316 ultimately enrolled. Participants were randomly assigned to receive either a placebo or varying doses of Prasinezumab (1,500 mg or 4,500 mg).

The progression of motor signs was assessed using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III score, a tool for evaluating the severity of motor symptoms in PD patients. This assessment was conducted over 52 weeks, allowing for longitudinal tracking of changes in motor function. Subpopulations were defined based on factors such as the participants’ use of monoamine oxidase B (MAO-B) inhibitors, Hoehn and Yahr stage, presence of rapid eye movement (REM) sleep behavior disorder, and motor subphenotypes.

Linear regression models were employed to analyze the relationship between Prasinezumab treatment and the progression of motor signs within each subpopulation. These analyses were adjusted for potential confounding variables, such as concurrent drug usage and genetic susceptibilities.

What did they find?

Participants in rapidly disease-progressing subpopulations exhibited a greater benefit from Prasinezumab treatment compared to those in non-rapidly progressing subpopulations. Specifically, individuals treated with MAO-B inhibitors at baseline showed a more pronounced treatment effect, as evidenced by a greater reduction in the progression of motor signs compared to individuals who did not receive the monoclonal antibody treatment. Similarly, participants with more advanced disease stages, as indicated by higher Hoehn and Yahr stage, also demonstrated a more favorable response to Prasinezumab treatment.  

These findings show that Prasinezumab is effective at slowing the progression of motor deficits in Parkinson's disease, and appears to have differential effects based on the underlying characteristics of patients, with greater benefits observed in subpopulations characterized by more rapid disease progression.

What's the impact?

This study identified a treatment capable of slowing down the progression of motor symptoms in PD, specifically in the subpopulation experiencing rapid progression. Research like this is critical to developing effective therapies for alleviating motor symptoms in individuals with PD.

ChatGPT, Creativity, and the Risks of Artificial Intelligence

Post by Rebecca Hill

The takeaway

ChatGPT, a promising tool for gathering and paraphrasing information, has recently been studied for its ability to mimic human creativity. However, ChatGPT has a darker side to it as well, taking information without consent, contributing to plagiarism, and spreading misinformation. 

What is ChatGPT?

Artificial intelligence (AI), or training computers to learn human skills, is an exciting new technology that can be used for a wide range of applications. Large language models are a relatively new type of AI, trained by large amounts of text to create new strings of similar text. One of the most popular new AIs is a chatbot called ChatGPT, powered by a large language model created by OpenAI that has been trained on a variety of text sources, from Wikipedia and journal articles to blogs across the internet. Users ask ChatGPT a question and it responds with paraphrased information, from a few sentences to several paragraphs long. However, these responses don’t automatically provide sources for their information, and sometimes even provide inaccurate information.

Can artificial intelligence be more creative than humans?

With this new technology, many are curious about its ability to not only mimic human language but also human skills such as decision-making and creativity. To measure creativity, researchers test both AI and humans with divergent thinking tasks – those that involve coming up with creative solutions to a problem. While one study claimed that ChatGPT created more original and elaborate solutions during these tasks than humans, another found that the best of the human ideas were better than the ChatGPT ideas. Studies like these have sparked active discussions around the idea of what constitutes creativity. Some researchers believe that AI chatbots like ChatGPT can create new ideas by making connections that humans often miss due to bias or fixed mindsets. Others argue that human creativity is too unique and complex to copy with AI and that since AI requires human input, it is not able to come up with any truly new ideas. Also, emotions are often seen as a crucial part to creativity, and AI doesn’t have the life experiences that humans channel into works of art.

The impact of AI on art

While ChatGPT is a text-based AI, there are also AIs that are used to create visual art, which has in turn triggered its own scientific discussion. Recent studies have found that people prefer art that was labeled as created by humans rather than AI, suggesting that there is a negative bias against AI-created artworks. While some of these studies purport that AI-created artwork is often indistinguishable from human-created, others emphasize the impact this has on the artists themselves. Artists spend years honing their craft and developing their artistic style, and many are insulted by the idea that art created by a person simply providing a prompt to an AI could be equivalent to their own art. Even more upsetting to many artists is that AI-created art is trained on the very same art that humans have spent hours creating, effectively stealing from the artists.

AI threatens the integrity of circulating information

While visual art being scraped for training data for AI is a hotly debated topic, the same can be said for the art of writing. Since ChatGPT is trained using data from the internet, it uses writing from any freely accessible source it can find. However, free to access does not mean free to use. A recent article points out that while there are exceptions to using copyright-protected material, these exceptions require not making money off of this use, and ChatGPT does have an option for users to pay for subscriptions for better access. Even more concerning is the use of ChatGPT in scientific writing, which can lead to bias, plagiarism, and the spread of misinformation. This can have dire consequences when it comes to medical and health research. While ChatGPT is a mystery to many and a fun tool for some, it is important to understand that it is more than a tool for gathering information. The foundations of ChatGPT are built on information not freely given, and the effects of it may be longer lasting and wider reaching than many have anticipated. 

References +

Bellaiche, L., Shahi, R., Turpin, M. H., Ragnhildstveit, A., Sprockett, S., Barr, N., Christensen, A., & Seli, P. (2023). Humans versus AI: Whether and why we prefer human-created compared to AI-created artwork. Cognitive Research: Principles and Implications, 8(1), 42. https://doi.org/10.1186/s41235-023-00499-6

Chiarella, S. G., Torromino, G., Gagliardi, D. M., Rossi, D., Babiloni, F., & Cartocci, G. (2022). Investigating the negative bias towards artificial intelligence: Effects of prior assignment of AI-authorship on the aesthetic appreciation of abstract paintings. Computers in Human Behavior, 137, 107406. https://doi.org/10.1016/j.chb.2022.107406

Guleria, A., Krishan, K., Sharma, V., & Kanchan, T. (2023). ChatGPT: Ethical concerns and challenges in academics and research. The Journal of Infection in Developing Countries, 17(09), 1292–1299. https://doi.org/10.3855/jidc.18738

Hubert, K. F., Awa, K. N., & Zabelina, D. L. (2024). The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks. Scientific Reports, 14(1), 3440. https://doi.org/10.1038/s41598-024-53303-w

Kane, S., Awa, K., Upshaw, J., Hubert, K., Stevens, C., & Zabelina, D. (2023). Attention, affect, and creativity, from mindfulness to mind-wandering. The Cambridge Handbook of Creativity and Emotions, 130-148.

Koivisto, M., & Grassini, S. (2023). Best humans still outperform artificial intelligence in a creative divergent thinking task. Scientific Reports, 13(1), 13601. https://doi.org/10.1038/s41598-023-40858-3

Runco, M. A. (2023). AI can only produce artificial creativity. Journal of Creativity, 33(3), 100063.

Teubner, T., Flath, C. M., Weinhardt, C., Van Der Aalst, W., & Hinz, O. (2023). Welcome to the Era of ChatGPT et al.: The Prospects of Large Language Models. Business & Information Systems Engineering, 65(2), 95–101. https://doi.org/10.1007/s12599-023-00795-x

Cognitive Network Processing in Chronic Pain

Post by Natalia Ladyka-Wojcik

The takeaway

The claustrum, a subcortical nucleus of the brain, may play an important role in both acute and chronic pain, such as the pain experienced by patients with migraines. This region is activated by painful stimulation and shows abnormal patterns of functional activity among migraine patients. 

What's the science?

Patients who suffer from chronic pain often report difficulties in cognitive processing, likely as a result of competing demands in the brain. Previous research suggests that pain contributes to cognitive load, or how much information can be processed at any given time, such that it increases activity across different cortical networks in a dysfunctional manner. One subcortical nucleus in particular called the claustrum, may be key to understanding cortical network disruptions related to chronic pain, as this region has been shown to respond to acute pain and shares vast structural and functional connections with the rest of the brain. In a sense, the claustrum may be a “hub” for different functional brain networks whose function is disrupted by chronic pain, such as in patients with migraines. This week in Current Biology, Stewart and colleagues aimed to further characterize the role of the claustrum in response to pain, by investigating how it modulates patterns of brain connectivity during cognitive task performance. 

How did they do it?

The authors conducted a series of analyses on functional magnetic resonance imaging (fMRI) data from both patients with migraines and healthy participants. First, the authors looked at the functional activity of the claustrum while healthy participants were exposed to heat stimulation on their forearm, to determine whether it scaled with pain experienced by participants in response to the stimulation compared to other neighboring brain regions. Next, they examined how claustrum responded to auditory cues that would predict the onset of painful heat stimulation in another set of healthy participants. This approach allowed the authors to determine if claustrum is responsive to pain-predictive cues, not just the pain itself. After examining the claustrum in the context of healthy participants, the authors shifted focus to a group of migraine patients, using a cognitive task to probe whether patients would show greater cortical network activity compared to healthy participants. This cognitive task called the multi-source interference task, required participants to identify a unique number in an array. Finally, they used a series of complex statistical approaches, including Partial Least Squares and Dynamic Causal Modeling, to model differences in patterns of functional brain connectivity related to cognitive performances among healthy controls and migraine patients. 

What did they find?

The authors found that in healthy adult participants the claustrum, especially in the left hemisphere, is responsive to the experience of heat pain and to cues associated with the onset of heat pain. Subsequently, when the authors compared patterns of activity in brain networks supporting cognitive performance between healthy participants and migraine patients, they found dysfunctional increases in activity among migraine patients. Importantly, these large-scale brain networks, such as the Fronto-Parietal Network, have been shown to have strong functional connections with the claustrum. Among patients with migraines, the authors found that right claustrum activity was significantly greater than that in healthy controls during pain stimulation and cognitive task performance. Finally, they also reported strengthened underlying projections in migraine patients from the right claustrum to a dorsolateral prefrontal cortex region associated with processing pain, even when the migraine patients were pain-free, consistent with a pattern of pathological engagement of the claustrum with chronic pain. These projections were confirmed structurally using diffusion-weighted imaging, a neuroimaging approach that allows researchers to map the movement of water molecules in brain tissue.    

What's the impact?

This study found that the claustrum, a subcortical nucleus involved in modulating different cognitive networks of the brain, is activated by acute pain in healthy individuals and is dysfunctional in patients with chronic pain. Altogether, the results of this study overwhelmingly implicate the claustrum in the relationship between cognitive impairment and chronic pain. Understanding chronic pain and finding ways to treat it is important, as an estimated 3.1 billion people globally suffer from chronic headache disorders like migraines, as well as countless more who experience other forms of chronic pain.