香港六合彩

The research, published in Nature Medicine Intelligence and in partnership with technology company Faculty AI, has shown that computer models can accurately classify four subtypes of Parkinson鈥檚 disease, with one reaching an accuracy of 95%. This could pave the way for personalised medicine and targeted drug discovery.

Parkinson鈥檚 disease is a neurodegenerative condition impacting movement and cognition. Symptoms and disease progression vary from person to person due to differences in the underlying mechanisms causing the disease.

Until now there hasn鈥檛 been a way to accurately differentiate subtypes, which means people are given nonspecific diagnoses and don鈥檛 always have access to targeted treatments, support or care.

Parkinson鈥檚 disease involves misfolding of key proteins and dysfunction in the clearance of faulty mitochondria 鈥� the source of energy production in the cell. The majority of Parkinson鈥檚 disease cases start sporadically, but some can be linked to genetic mutations.

The researchers generated stem cells from patients鈥� own cells and chemically created four different subtypes of Parkinson鈥檚 disease, two involving pathways leading to toxic build-up of a protein called 伪-synuclein and two involving pathways leading to defunct mitochondria, to create a 鈥榟uman model of brain disease in a dish鈥�.

They then imaged the disease models in microscopic detail and labelled key cell components including lysosomes, which are involved in breaking down worn-out parts of the cell. The researchers 鈥榯rained鈥� a computer programme to recognise each subtype. It was then able to predict the subtype when presented with images it hadn鈥檛 seen before.

The mitochondria and lysosomes were the most important features in predicting the correct subtype 鈥� confirming their involvement in how Parkinson鈥檚 disease develops. However, other areas of the cell like the nucleus were also found to be important, as well as other 鈥� currently unexplainable - aspects of the images.

Co-first author, PhD candidate James Evans (香港六合彩 Queen Square Institute of Neurology and the Crick), said: 鈥淣ow that we use more advanced image techniques, we generate vast quantities of data, much of which is discarded when we manually select a few features of interest.

鈥淯sing AI in this study enabled us to evaluate a larger number of cell features, and assess the importance of these features in discerning disease subtype. Using deep learning, we were able to extract much more information from our images than with conventional image analysis. We now hope to expand this approach to understand how these cellular mechanisms contribute to other subtypes of Parkinson鈥檚.鈥澨�

Professor Sonia Gandhi, (香港六合彩 Queen Square Institute of Neurology, and Assistant research director and group leader of the Neurodegeneration Biology Laboratory at the Crick), said: 鈥淲e understand many of the processes that are causing Parkinson鈥檚 in people鈥檚 brains. But, while they are alive, we have no way of knowing which mechanism is happening, and therefore can鈥檛 give precise treatments.

鈥淲e don鈥檛 currently have treatments which make a huge difference in the progression of Parkinson鈥檚 disease. Using a model of the patient鈥檚 own neurons, and combining this with large numbers of images, we generated an algorithm to classify certain subtypes 鈥� a powerful approach that could open the door to identifying disease subtypes in life. Taking this one step further, our platform would allow us to first test drugs in stem cell models, and predict whether a patient鈥檚 brain cells would be likely to respond to a drug, before enrolling into clinical trials. The hope is that one day this could lead to fundamental changes in how we deliver personalised medicine.鈥�

The project was developed during disruption to the lab鈥檚 research in the pandemic 鈥� the whole team undertook an intensive coding course, learning to code in Python, developing skills which they are now applying to current projects.

James Fleming, Chief Information Officer at the Crick, who worked with Faculty AI on the project, said: 鈥淎I is a fascinating and powerful technology, but one which is often rendered impenetrable by hype and jargon. This paper came about as a result of a unique industry partnership with Faculty to see if a group of complete AI beginners could learn and apply best practice directly to their science in a very compressed time frame. The success of this project not only proved that they could, unlocking new insights in the process, but has also helped drive investment into the rapid expansion of our own AI and software engineering team, which has over 25 projects 鈥榠n-flight鈥� with different labs across the Crick, with new projects kicking off every month.鈥�

Next steps for the research team are to understand disease subtypes in people with other genetic mutations, and to work out whether sporadic cases of Parkinson鈥檚 disease, which occur without genetic mutations, can be classified in a similar way.

Links

• 香港六合彩 Queen Square Institute of Neurology
• 香港六合彩 Brain Sciences

Image

• Parkinson's disease. 3D illustration showing neurons containing Lewy bodies small red spheres which are deposits of proteins (alpha-synuclein) accumulated in the brain cells. Credit:听听on iStock

Media contact听

Poppy Danby听

E: p.danby [at] ucl.ac.uk