An international team of scientists has detected proteins associated with Parkinson’s disease in eye cells using a artificial intelligence (AI) that they developed to study the ocular fluid and that has allowed them to measure the aging of the eyeswhich opens new possibilities for the treatment of a large number of eye diseases.
Researchers from Stanford Medicine participated in the study and after observing almost 6,000 proteins in this liquid, they discovered that they can use 26 of them to predict aging. By using artificial intelligence, they developed a “eye aging clock”, which indicates which proteins accelerate aging in each disease and reveals new potential targets to which therapies can be directed.
The watch revealed that diseases such as diabetic retinopathy and uveitis cause accelerated aging in specific cell types, specifically vascular cells in late-stage diabetic retinopathy, retinal cells in retinitis pigmentosa, and immune cells in uveitis. In addition, they also detected proteins associated with Parkinson’s within the ocular fluid, which, they say, could help diagnose Parkinson’s at an early stage.
“At the molecular level, patients present different manifestations, even with the same disease. “With a molecular fingerprint like the one we have developed, we could choose drugs that work for each patient.”
“This is one of the best connections ever made to suggest that the disease triggers accelerated aging,” said Dr. Vinit Mahajan, professor of ophthalmology and lead author of the study, which was published in Cell. Researchers aim to apply the clock method to other body fluids to develop more effective drugs for different diseases.
Mahajan and his team developed the TEMPO technique, or expression tracking of multiple protein origins, which allows scientists to understand the cellular origin of disease-causing proteins in the hope of developing new personalized medical treatments with the ability to attack these pathological cells.
“The first step in developing any type of successful therapy is understanding the molecules,” explains Mahajan. “At the molecular level, patients present different manifestations, even with the same disease. With a molecular fingerprint like the one we have developed, we could choose drugs that work for each patient.”
Diseases associated with significant molecular aging
The researchers analyzed liquid biopsies taken from the aqueous humor (fluid between the lens and the cornea) while patients remained locally anesthetized during surgery, with the goal of better understanding which cellular processes contribute to the onset of various eye diseases.
The fluid was collected from patients with three types of eye diseases: diabetic retinopathy, which is characterized by leaks in the blood vessels of the eye that cause vision loss; retinitis pigmentosa, which causes light-sensitive cells in the back of the eye to break down; and uveitis, inflammation inside the eye.
Using ocular fluid from 46 healthy patients, Mahajan and his team trained an artificial intelligence algorithm to predict the patient’s age. They then ran the algorithm through the 5,953 proteins present in the fluid to see if a subset of these proteins could predict the patient’s age and identified 26 that could do so when used as a group.
By comparing diseased eye fluid to healthy fluid, they found that patients with diseased eyes had proteins that indicated greater age: 12 years older in patients with early-stage diabetic retinopathy, 31 years in those with late-stage diabetic retinopathy, 16 years in patients with retinitis pigmentosa, and 29 years in patients with uveitis.
The model was able to accurately predict the age of healthy eyes and showed that the diseases were associated with significant molecular aging. In the case of diabetic retinopathy, the degree of aging increased with the progression of the disease and accelerated up to 30 years in people who suffered from severe (proliferative) diabetic retinopathy.
The researchers also detected several proteins associated with Parkinson’s disease. These proteins are usually identified post-mortem and the available diagnostic methods are not capable of detecting them, so the detection of these markers in ocular fluid could allow a early diagnosis of Parkinson’s and therapeutic monitoring of patients.
Treatment targeting prematurely aging cells
They also found that some cells that are usually the target of treatment are not those most involved in the disease, which indicates the need to reevaluate therapies. For example, diabetes drugs normally target blood vessel cells because they become leaky with the disease, but they found a large increase in proteins from healthy diabetic retinopathy, to advanced stage diabetic retinopathy, in the macrophages, an immune cell that eliminates dead cells.
They also found that some cells had shown accelerated aging before symptoms appeared. Early treatment of the molecular pathway, Mahajan said, could prevent disease damage before it becomes irreparable. According to the expert, directing therapies to both aged and diseased cells could improve the effectiveness of treatmentbecause the two seem to act separately, but simultaneously, to damage the eye.