Patterns of Neural Network Degradation Differ in Alzheimer's Disease and Normal Aging
Key findings
- Preferential degradation of cognitive networks, especially the default and dorsal attention networks, is statistically discernible in early symptomatic stages of autosomal dominant Alzheimer's disease (AD) and is magnified in more advanced disease
- A nascent form of the preferential degradation of cognitive networks is seen in participants with preclinical AD
- The AD-related pattern contrasted with what is seen in aging-focused comparisons, where visual networks are degraded to a similar or larger degree than cognitive networks, with little change in the motor network
- By understanding the distinct patterns of network degradation in aging and AD, it may be possible to create functional magnetic resonance imaging metrics that could better isolate AD-related changes in connectivity from those that are due to normal aging
Functional connectivity magnetic resonance imaging (MRI) has become a tool for examining neural network dysfunction in patients with neurodegenerative diseases including Alzheimer's disease (AD). It's well established that patients with AD show early degradation of the default network, but the disease's effects on other cognitive and noncognitive networks has been difficult to determine.
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A major problem is that the characteristic changes in default network connectivity in AD are also seen in many other disease states and with normal aging. Now, researchers from the Dominantly Inherited Alzheimer Network (DIAN) have observed a pattern of connectivity degradation in AD that's distinct from the pattern seen with normal aging.
What's more, the research team including physician Jasmeer P. Chhatwal, MD, PhD, and researcher Aaron Schultz, PhD, in the Department of Neurology, and Reisa A. Sperling, MD, affiliated faculty of the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital, suggests in Brain that it may be possible to develop composite connectivity measurements that facilitate the use of functional MRI for detecting early AD in older patients.
Study Participants and Methods
The researchers analyzed functional MRI data from two groups:
- 112 individuals with mutations that put them at high risk of autosomal dominant AD
- 66 (average age 34) had a global Clinical Dementia Rating (CDR) of 0
- 29 (average age 44) had a CDR of 0.5
- 17 (average age 49) had a CDR ≥1
- 170 cognitively normal participants from the Harvard Aging Brain Study
- 81 were younger adults (average age 22)
- 59 were elderly (average age 70) and were considered free of signs of AD (AD−) based on MRI of the hippocampus and two forms of positron emission tomography
- 30 were elderly (average age 79) and had signs of AD on imaging (AD+)
The team examined connectivity changes in:
- Four cognitive networks implicated in AD: default, salience, dorsal attention and control
- Three noncognitive networks: motor, primary visual and extrastriate visual
Network Degradation in Autosomal Dominant AD
In all networks except the extrastriate visual network, there were significant differences in network degradation across the CDR0, CDR0.5 and CDR1+ groups. Cognitive networks, especially the default and dorsal attention networks, were more degraded than motor and sensory networks.
Network Degradation in Preclinical AD
Compared with cognitive normal elderly adults who were AD− on imaging, those who were AD+ showed decreased connectivity in the default and salience networks. No significant differences in primary visual, extrastriate visual or motor network connectivity were observed between AD− and AD+ participants.
Network Degradation in Aging
Compared with young cognitively normal participants, cognitively normal elderly adults who were AD− showed decreased connectivity in all networks except the motor network.
Composite Connectivity Measurement
Because visual and cognitive networks were similarly degraded with normal aging, the researchers explored whether they could distinguish AD− related network degradation from age-related degradation. They were able to so by calculating the average of whole-network measurements across the four cognitive networks, then adjusting for visual network connectivity.
Research Implications
These findings are further evidence that aging and AD are distinct pathophysiologies—AD is not an accelerated form of aging. Formalizing the differential patterns of network degradation in aging and AD may yield multi- or inter-network connectivity measurements that can facilitate detection of preclinical AD in elderly adults.
Such measures might also increase the specificity of functional MRI for other neurodegenerative diseases, allowing investigators to enrich clinical trial populations by reducing the influence of common confounding conditions.
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