A new study has revealed the possibility of using artificial intelligence models to screen for autism and check the severity of the condition, based on an image of the retina.
Previous studies have linked changes in retinal nerves with altered brain structures, hence autism spectrum disorder (ASD).
“Individuals with autism spectrum disorder have structural changes in the retina that likely reflect changes in the brain, including visual pathway abnormalities through fetal and anatomical connections,” the researchers wrote in their new paper.
In the study, a team from Yonsei University College of Medicine in the Republic of Korea wanted to know if artificial intelligence could detect autism spectrum disorder in retinal patterns.
The model was trained on images where the AI was told whether the individual was autistic or not.
Next, the AI was asked to analyze the retinas of 958 children with an average age of 7 and 8 years overall, half of whom had been diagnosed with autism.
He was able to achieve an excellent score in identifying those with autism. The artificial intelligence was not good at predicting the severity of symptoms from retinal images, as it was only 48 to 66% accurate.
In a study published last year, researchers were able to link the retina's response to light to cases of attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder, another example of how the eyes act as a kind of mirror of an individual's brain activity.
“The results of this study suggest that retinal images may serve as a viable filter as an objective way to screen for autism and possibly symptom severity,” the researchers wrote.
The research was published in JAMA Network Open.
Scientists provide new insights into the state of cells early in Alzheimer's disease
The origin of Alzheimer's disease, which affects 30 million people around the world, remains unclear despite international research efforts and significant progress in research.
However, identifying the causative factors of this incurable neurological disease is essential to finding better ways to diagnose it, delay its onset, and prevent its progression.
Alzheimer's disease is an incurable disease that usually appears after the age of 65 years. However, changes in the brain begin 20 years before the onset of the disease.
“We think that mitochondrial dysfunction (or mitochondria, organelles that convert food products into energy) can occur 20 years before a person shows symptoms of the disease,” explains Montse Soler Lopez, head of the Structural Biology Group at the European Synchrotron Radiation Facility (ESRF). ;.
For a long time, researchers have focused on amyloid plaques in the brain as a possible cause of the disease. However, this hypothesis is currently being reconsidered.
Soler Lopez's team, in collaboration with scientists at the Institute of Structural Biology at the University of Grenoble Alpes and researchers at the European Molecular Biology Laboratory (EMBL), is conducting a new line of research focusing on factors of aging, such as mitochondrial dysfunction.
Mitochondria are often referred to as the “powerhouse of cells.” Because of its essential role in energy production. Over time, the mitochondria suffer from oxidative stress, and this leads to malfunction.
Recent findings suggest that people with Alzheimer's may show an accumulation of amyloids within the mitochondria, challenging the previous belief that amyloids were only present outside neurons.
During the initial stages of Alzheimer's disease, amyloids usually exist as amyloid beta oligomers before turning into fibrils.
Soler-Lopez and her team are investigating what happens inside the mitochondria during these early stages.
Energy is produced by the mitochondria through the respiratory chain, which consists of five protein complexes that must work cooperatively and efficiently to generate energy.
Among these complexes, Complex I, or CI for short, is of great importance as the first, largest, and most important enzyme in the respiratory chain.
For CI to function properly, assembly factors are essential, and an assembly factor complex known as “mitochondrial complex I,” or MCIA, which consists of three essential proteins - ECSIT, ACAD9, and NDUFAF1, plays a pivotal role in coordinating CI assembly for optimal performance.
Soler-Lopez and her colleagues discovered that ECSIT plays a role in deactivating the fatty acid oxidation function of ACAD9 through the process of lipid removal, redirecting the protein to its role in CI assembly. This holds importance for the coordination and regulation of cellular energy mechanisms.
Their observations also show that an essential requirement for the proper formation of "mitochondrial complex I" It is the dephosphorylation of ECSIT, where dephosphorylation enables ACAD9-ECSIT interaction.
Experimental results revealed that in purified mitochondria, ECSIT dephosphorylation becomes more pronounced in the presence of amyloid beta oligomer accumulation.
In turn, this amyloid accumulation leads to hyperactivity of the CI complex, according to which the stability of “mitochondrial complex I” increases. Dephosphorylated which helps in correct CI formation.
These results differ from previous studies that included brain tissue from Alzheimer's patients, which indicated that CI should be discontinued. “We observed just the opposite, suggesting that in the early stages of the disease, amyloid beta oligomers stimulate an overactive CI complex, creating a harmful cycle that ultimately leads to a weakening of the respiratory chain,” Soler-Lopez explains.
She concluded, “These results provide insight into the role of amyloid beta oligomers in the onset of the disease, which may open new ways to treat Alzheimer’s disease in its early stages.”
The results were published in the journal Nature Communications.
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