Periodic Reporting for period 1 - TRACE-AD (Tracking the Effects of Amyloid and Tau Pathology on Brain Systems and Cognition in Early Alzheimer’s Disease)
Période du rapport: 2019-04-01 au 2021-03-31
Alzheimer’s disease is a tremendous burden for individual patients, relatives and the health care system. Despite intensive research efforts and drug development, there are still no therapies that have been shown to slow down or stop the disease in a phase 3 trial. So far, most clinical trials have focused on patients in the symptomatic late stages of AD where the neuronal damage is already severe and probably irreversible. Thus, it is imperative to focus on earlier stages of the disease. In early stages, the two hallmark pathologies of Alzheimer’s disease – beta-amyloid and tau – can be found in circumscribed anatomical systems before they eventually affect the entire human brain. Overall, AD pathology leads to changes in brain function, cognitive impairment where the core deficit is memory decline and loss of grey matter. However, due to our limited understanding how AD pathology affects brain and cognitive function early in the disease, it is not known when disease-modifying therapies should target beta-amyloid and/or tau to effectively slow down or even reverse symptoms. Likewise, there is an urgent need for sensitive markers that can identify individuals who are at an early asymptomatic stage, but are likely to deteriorate in the coming years, because such individuals are likely to benefit most from early intervention trials. Finally, we need sensitive markers of treatment response that can indicate the benefit of a treatment.
Here we employed the powerful combination of ultrahigh-field magnetic resonance imaging (MRI) with positron emission tomography (PET) and novel memory assessments via smartphones to unravel the early functional, structural and cognitive changes related to A and tau. The aim of the proposal is a more profound understanding of the earliest stages of the disease as well as novel cognitive and imaging markers that improve patient selection and stratification as well as the assessment of treatment response in future clinical AD trials.
Here we employed the powerful combination of ultrahigh-field magnetic resonance imaging (MRI) with positron emission tomography (PET) and novel memory assessments via smartphones to unravel the early functional, structural and cognitive changes related to A and tau. The aim of the proposal is a more profound understanding of the earliest stages of the disease as well as novel cognitive and imaging markers that improve patient selection and stratification as well as the assessment of treatment response in future clinical AD trials.
In the beginning of the project, we have optimized imaging sequences that allowed us to image the human brain of individuals at risk for Alzheimer’s disease at very high resolution. For our project, this was particularly important in order to elucidate fine-grained changes in brain structure as well as to understand which regions are active during certain cognitive tasks. We have then invited 170 participants for brain scans which had already participated in a large study in Lund before, in the Swedish BioFINDER study. Using brain scans from the Swedish BioFINDER study, we have analyzed the amount of Alzheimer’s disease pathology within brain regions, the connections between and activity in different brain regions, the thickness and volume of brain regions and have investigated the thinking and memory capacities of our participants. In addition, our participants downloaded a smartphone app that allowed them to complete memory tests every two weeks within the coming year.
Using this dataset, we were interested how Alzheimer’s disease pathology affects the human brain and when different measures are affected. We found that functional measures were affected early and that these changes were associated with beta-amyloid and tau pathology. Interestingly, the brain system that was primarily involved in memorizing objects was particularly affected early on in our participants.
The second question was whether and until when the cognitive impairment that is experienced by Alzheimer’s disease patients could be reversible. While we cannot answer this definitely with magnetic resonance imaging, we asked whether the cognitive impairment is due to brain atrophy with the idea that this would be indicative that symptoms might not be reversible. We found that in early disease stages there was no severe atrophy and that subtle atrophy was not associated with cognitive impairment. However, in later stages, atrophy was more severe and did already explain part of the cognitive impairment of our participants. This analysis also showed that atrophy of the posterior hippocampus could be an interesting marker to identify individuals in early disease stages. Taken together, our results showed evidence that early cognitive impairment in Alzheimer's disease might be reversible and yielded potential atrophy markers.
Our last question was which brain measures (Alzheimer’s pathology, connectivity, atrophy) were related to cognitive worsening. Here we found that it was feasible to collect cognitive data via a smartphone app and that the collected data was reflecting measures of tau pathology but was also in line with more extensive neuropsychological assessments which had been done at the memory clinic. Furthermore, we asked individuals to perform tests every two weeks for an entire year and analyzed how the memory of the participants developed over time. In our remaining analysis we will now analyze whether and which brain measures can predict short-term cognitive decline within one year.
Using this dataset, we were interested how Alzheimer’s disease pathology affects the human brain and when different measures are affected. We found that functional measures were affected early and that these changes were associated with beta-amyloid and tau pathology. Interestingly, the brain system that was primarily involved in memorizing objects was particularly affected early on in our participants.
The second question was whether and until when the cognitive impairment that is experienced by Alzheimer’s disease patients could be reversible. While we cannot answer this definitely with magnetic resonance imaging, we asked whether the cognitive impairment is due to brain atrophy with the idea that this would be indicative that symptoms might not be reversible. We found that in early disease stages there was no severe atrophy and that subtle atrophy was not associated with cognitive impairment. However, in later stages, atrophy was more severe and did already explain part of the cognitive impairment of our participants. This analysis also showed that atrophy of the posterior hippocampus could be an interesting marker to identify individuals in early disease stages. Taken together, our results showed evidence that early cognitive impairment in Alzheimer's disease might be reversible and yielded potential atrophy markers.
Our last question was which brain measures (Alzheimer’s pathology, connectivity, atrophy) were related to cognitive worsening. Here we found that it was feasible to collect cognitive data via a smartphone app and that the collected data was reflecting measures of tau pathology but was also in line with more extensive neuropsychological assessments which had been done at the memory clinic. Furthermore, we asked individuals to perform tests every two weeks for an entire year and analyzed how the memory of the participants developed over time. In our remaining analysis we will now analyze whether and which brain measures can predict short-term cognitive decline within one year.
Our project showed further evidence that cognitive impairment in early stages of Alzheimer’s disease might be reversible. In addition, we showed that more fine-grained anatomical atrophy measures of brain regions that are important for memory functioning might be meaningful to select study participants or to monitor the effect of a potential treatment. Furthermore, we showed that it might be possible to acquire cognitive data from study participants at risk of Alzheimer’s disease at high frequency via memory tasks on their personal smartphones. At the end of the project, we aim for markers that can predict short-term cognitive decline within one year and hope that our findings can help finding participants for future clinical trials and can help to assess treatment effects.