National Institute on Aging

05/09/2024 | News release | Distributed by Public on 05/09/2024 05:35

Brain scans helped spot hidden forms of dementia in people with Alzheimer’s

Certain cerebral structures seen on brain scans may signify whether the thinking and memory problems a person with Alzheimer's disease experiences are also due to other forms of dementia. According to an NIA-funded study, these brain scan signatures may be combined with demographic, clinical, cognitive, and genetic information to help researchers better understand the underlying factors that influence a person's dementia, as well as improve Alzheimer's research. Results of the study were published in Alzheimer's & Dementia.

Alzheimer's is the most common form of dementia. The presence of elevated levels of abnormal amyloid and tau proteins found in the brain are among several hallmarks used to determine whether a person may have the disease. In most cases, the presence of amyloid and tau proteins is accompanied by one or more other changes to the brain that may cause cognitive decline and dementia. These dementia-related pathologies include clumps of α-synuclein proteins associated with Lewy body dementia (LBD), clusters of transactive response DNA-binding proteins (TDP-43) linked to limbic-predominant age-related TDP-43 encephalopathy, and amyloid deposits found in brain blood vessels that are hallmarks of cerebral amyloid angiopathy (CAA).

Studies have shown that these co-pathologies may contribute to the dementia experienced by people with Alzheimer's. However, as there are currently no effective biomarkers for these additional factors, the ability to detect them in people while they are alive has been elusive. In this study, a research team led by the University of California, San Francisco sought to use magnetic resonance imaging brain scans to detect the presence of these other brain pathologies in living subjects, and thus improve the way researchers evaluate each person's dementia.

The team analyzed three-dimensional brain scans along with clinical and autopsy reports from 214 older adults to identify unique imaging signatures for LBD, TDP-43, and CAA. Combining these signatures with demographic and clinical information, as well as results from cognitive, biomarker, and genetic tests, they created a computer model to detect the possible presence of these other forms of dementia in people with Alzheimer's. The model's performance was then checked against the results of autopsy reports.

Initial results showed that the model was 81% accurate for detecting LBD; 84% accurate for TDP-43; and, depending on how it was calculated, 76% to 93% accurate at detecting CAA. These results were more accurate than a reference model which did not include the brain scan data.

Next, the team tested the new model's ability to detect the other dementias on a separate group of people. The results were that 289 of these subjects were diagnosed with normal cognition, 376 had mild cognitive impairment, and 198 had Alzheimer's. The model detected TDP-43 in 49% and LBD in 24% of the participants who had Alzheimer's-like levels of amyloid as detected on other types of brain scans or by tau detected in cerebrospinal fluid samples. Moderate and severe CAA was detected in 32% of these participants and mild, moderate, or severe CAA was detected in 98% of them. These frequencies were similar to those reported in other studies based on autopsy analysis.

Further analysis of this second dataset supported the idea that these other forms of dementia may contribute to the cognitive decline experienced with Alzheimer's. The presence of amyloid and tau appeared to contribute to 26% to 36% of cognitive decline. Meanwhile, the presence of LBD, TDP-43, and CAA contributed to 24% to 25% of decline, and 8% to 12% of decline appeared to be due to demographics.

Lastly, the effects of using the model in screening participants for Alzheimer's clinical trials were evaluated. Overall, use of the model increased the sensitivity of the trial to detect changes in cognition related to Alzheimer's. This could help decrease the number of participants needed to test the effectiveness of treatments designed to target amyloid proteins.

Overall, this study's findings both support the role that LBD, TDP-43, CAA, and other forms of dementia may play in the cognitive decline experienced by people with Alzheimer's and provide, for the first time, a method for detecting risks for these dementias. Having a brain scan-based method for detecting these other forms of dementia could enable more personalized, precision medicine approaches in Alzheimer's clinical trials because improved diagnostic tools may help researchers better identify the most appropriate participants as well as treatments targeted to specific pathologies. Future studies will need to validate the model in larger and more diverse populations.

This research was supported in part by NIA grants AG024904, AG068057, AG058676, AG074855, AG066444, AG00561, AG026276, AG003991, AG043434, AG016976, AG003991, AG028383, AG013854, AG047366, AG005133, AG005681, AG024904, AG068057-01, and AG058676.

These activities relate to the following NIH AD+ADRD Research Implementation Milestones:

Reference: Tosun D, et al. Identifying individuals with non-Alzheimer's disease co-pathologies: A precision medicine approach to clinical trials in sporadic Alzheimer's disease. Alzheimer's & Dementia. 2024;20(1):421-436. doi: 10.1002/alz.13447.