Understanding Mild Cognitive Impairment: Insights from the European Ai-Mind Study
Mild Cognitive Impairment (MCI) is a condition that affects millions of people worldwide, with approximately 10 million subjects affected in Europe alone. In Italy, over 950,000 people are living with MCI, which is characterized as an intermediate stage between normal brain aging and pathological degeneration, such as dementia. According to Professor Paolo Maria Rossini, director of the Department of Neuroscience and Neurorehabilitation at Irccs San Raffaele in Rome, MCI constitutes a clearly increased risk of developing dementia, but only in a part of the subjects, which varies between 30 and 50%, is a real progression observed in the following years.
Key Findings from the Ai-Mind Study
The European Ai-Mind study, launched in 2021 and financed by the European Commission with approximately 14 million euros under the Horizon 2020 programme, has shed new light on MCI. The study, which involves 15 partners from 8 European countries and over 100 researchers, has found that approximately 10% of subjects with MCI progressed towards a form of dementia over 24 months, while approximately 20% showed a significant cognitive decline compared to time 0, although still remaining in a MCI condition. These findings are based on the analysis of a sample of 1,022 subjects followed in four European clinical centers (Madrid, Oslo, Helsinki, and Rome).
Importance of Early Diagnosis and Geographical Differences
The study highlights the importance of early diagnosis and the need to identify subjects at high risk of developing dementia. “Since MCI itself does not imply a loss of autonomy or clinically relevant deficits, it would be extremely important to be able to identify as early as possible who, within this population, has a high risk of developing dementia and who does not,” added Rossini. The study also reveals evident differences between the populations of Northern Europe and those of the Mediterranean area, concerning genetically determined risk profiles, the presence of amyloid in the plasma, and the definition and clinical staging of MCI. These geographical differences persist even after controlling for the main demographic factors and suggest that, in addition to the genetic background, variables related to the educational level, diagnostic strategies, and clinical practice paths of the different healthcare systems come into play.
Using Artificial Intelligence to Identify High-Risk Subjects
The vast amount of socio-demographic, clinical, genetic, biological, neuropsychological, and neurophysiological data collected as part of the project will be subjected to analysis using advanced artificial intelligence algorithms. “We expect the identification of characteristics capable of precisely identifying subjects at high risk of developing dementia in general and Alzheimer’s disease in particular,” concluded Rossini. The study’s findings and the use of artificial intelligence to analyze the data will contribute to the development of more effective diagnostic tools and personalized treatment plans for individuals with MCI.