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Zawartość zarchiwizowana w dniu 2024-05-30

Combining sensitive biomarkers for early diagnosis of AD: A multi-modal approach

Final Report Summary - AD BIOMARKERS (Combining sensitive biomarkers for early diagnosis of AD: A multi-modal approach)

The aim of this project is to assess the ability of different neuroimaging biomarkers to improve the diagnosis of mild cognitive impairment due to Alzheimer’s disease and Parkinson’s disease. Specifically, our goals were to use structural magnetic resonance imaging (MRI), diffusion tensor imaging and resting-state functional MRI to detect patterns of brain abnormalities that can explain how the development of cognitive dysfunction can ultimately lead to dementia in two of the most common neurodegenerative disorders. Regarding Alzheimer’s disease, we have been able to show that scores rating medial temporal atrophy on structural MRI are useful to distinguish these patients from healthy controls as well as subjects with mild cognitive impairment who are in the prodromal stages of the disease. Specifically, a good diagnostic sensitivity of 84.5% and 75.8% was achieved for classifying patients with Alzheimer’s disease and patients with mild cognitive impairment who developed dementia after one year, respectively. We also observed that specific demographic, clinical and genetic variables had a significant influence on the classifications, with older patients with an earlier disease onset and carrying the apolipoprotein e4 allele showing greater medial temporal atrophy. We provided recommendations for the use of medial temporal atrophy scales to improve the diagnosis of Alzheimer’s disease in a clinical setting. Regarding Parkinson’s disease, so far we have shown that patients with mild cognitive impairment have widespread cortical thinning in frontal, temporal, parietal and occipital areas compared to healthy controls. This pattern of brain structural abnormalities was more severe and extensive than that observed in Parkinson’s patients without cognitive problems, suggesting that the presence of mild cognitive impairment in Parkinson’s disease could increase the vulnerability of these patients to develop dementia. In addition to cortical thinning, we also found that Parkinson’s patients with cognitive impairment show changes in the communication between brain regions. Specifically, their networks are weaker, less efficient and poorly organized compared to controls or cognitively normal patients. Using cerebrospinal fluid biomarkers, we found that Abeta-42 levels are significantly decreased in patients with mild cognitive impairment compared with controls after adjusting for covariates and that lower α-synuclein levels are associated with executive, attention and global cognitive performance. Finally, in two subsequent studies we have found that nigrostriatal dopaminergic deficits are associated with executive impairment in early Parkinson’s disease and that executive deficits are associated with the strength of the resting-state fronto-parietal network.
Altogether, our findings show that mild cognitive impairment is associated with severe brain abnormalities both in Alzheimer's and Parkinson's diseases. They also suggest that medial temporal atrophy and amyloid pathology, two of the most important hallmarks of Alzheimer's disease, can be found in Parkinson's patients, particularly in those with cognitive deficits. These results suggest that different neurodegenerative disorders might share common disease propagation mechanisms. The information obtained in the different studies carried out in this project will be applied in a clinical environment to improve the diagnosis of mild cognitive impairment due to Alzheimer’s and Parkinson’s diseases. Most of our neuroimaging analyses can be automatized to produce disease patterns that can be used by clinicians in their daily evaluations. Hence, we hope to improve early diagnosis and identify patients with greater risk of developing dementia so that they can be treated before irreversible neuronal damage has taken place. This will reduce the socio-economic impact of these diseases.