What Makes fMRI Special for Alzheimer’s

Functional magnetic resonance imaging (fMRI) is like a camera for the brain. It’s non-invasive, meaning it doesn’t require surgery, and it can give us a picture of brain activity by tracking blood flow. Specifically, its most widely adopted signal, BOLD (blood-oxygen-level-dependent), allows us to see how different parts of the brain are communicating with each other, in other words how synchronized they are.

In Alzheimer’s disease, changes in synchrony across brain regions, their ‘connectivity’, appear years before any symptoms start. This means fMRI could be a powerful tool for spotting the disease early, long before symptoms appear. That’s crucial because earlier detection means we can start treatments sooner. Moreover, understanding these connectivity changes also provides valuable insights into the later stages of the disease, enabling the development of targeted therapies to manage symptoms and improve the quality of life for those already affected. By leveraging brain imaging and animal models, we aim to uncover mechanisms that can address both early intervention and improve therapeutic strategies for later-stage Alzheimer’s disease.

The Role of Mouse Models in Alzheimer’s Research

Despite all the progress, using fMRI to study Alzheimer’s disease in humans has been tough due to the complexity of the disease and the individual differences between patients. This is where mouse models come in. Mice have similar biological systems to us, can be genetically modified to develop Alzheimer’s, and can be studied in a standardized and controlled environment on a much more tractable time scale (~2 years lifespan). This means we can gain a better understanding of the disease progression, assess the effectiveness of treatments, and monitor their prognosis.

In our study, we assess brain changes over the lifespan of a novel mouse model of Alzheimer’s disease, from very young (and asymptomatic) to very old (and symptomatic) animals. The mouse model used in this study carries multiple genetic mutations in an attempt to recapitulate the complex profile of Alzheimer’s disease, whilst critically avoiding some of the problems with earlier models. This results in a ‘milder’ progression of the pathology, gifting us a longer time window for investigating brain changes. Alongside measuring brain changes in Alzheimer’s mice over their lifespan, we also investigate the effects of a treatment aimed at rescuing brain dysfunction in old mice. Both the mouse model adopted here and the treatment used were recently established in the laboratory led by Dr Stephen Strittmatter, a key collaborator on this project.

What We Found in Our Study

We measured changes in brain connectivity in these mice from the early to late stages of Alzheimer’s and compared them to healthy mice, matched in age. Here are some key takeaways:

1. Different Trajectories of Brain Activity: In healthy mice, connectivity increased as they aged, peaking in middle age before slowly decreasing in old mice, following an ‘inverted U-shape’ profile. Alzheimer's mice, instead, showed a much smaller increase in connectivity, and this was shifted much later in life compared to healthy mice, alongside a more drastic decrease as they aged. This suggests that Alzheimer's disrupts the normal pattern of brain aging. Notably, these changes were apparent at a time when symptoms were not yet detectable, providing evidence of brain changes preceding behavioral changes, and indicating the potential for therapeutic intervention before cognitive decline becomes evident.
2. Specific Brain Networks Are Affected: Changes in brain connectivity were especially noticeable in certain brain networks known for their roles in thinking and memory.
3. Treatment Holds Promise: We also tested a drug called BMS-984923, which targets a specific receptor for excitatory signals in the neurons (mGluR5). When given to older Alzheimer's mice that were already symptomatic, this drug significantly improved their brain connectivity, restoring it to almost the same level of age-matched healthy mice. This suggests that this approach might be useful for patients we can currently identify using existing diagnostic methods.

Why This Matters for Patients

Our findings have several exciting implications for diagnosing and treating Alzheimer’s:

• Enhanced Understanding of Aging Trajectories: Our findings reveal brain changes over time in both healthy mice, following a distinct ‘inverted U-shape’ profile, and Alzheimer’s mice, deviating from the healthy trajectory. This novel and interesting background provides crucial insights into the temporal continuum of Alzheimer’s disease progression, atop normal aging.
• Early Detection Potential: By identifying the changes in connectivity that occur before symptomatic stages in Alzheimer's mice, we highlight the possibility of detecting Alzheimer’s early. This can allow for timely interventions which could potentially slow down the disease progression.
• Improved Treatment Strategies: The observed disparity in connectivity patterns between healthy and Alzheimer’s mice underscores the importance of developing targeted interventions. Our research provides evidence that improving brain connectivity in very late stages of the disease, when symptoms are apparent, could be a key strategy to rescue brain deficits in Alzheimer’s.

Looking Ahead: The Future of Alzheimer’s Research

Our study shows the power of combining advanced brain scans with detailed mouse studies to uncover the mechanisms of Alzheimer’s. As we continue to refine these techniques, we hope to move ever closer to early diagnosis and more effective treatments for all patients.

One exciting future direction is to use these findings to guide human clinical trials. While incorporating fMRI into routine check-ups for individuals at risk of Alzheimer’s may not be feasible due to its high cost, this research holds promise for deepening our understanding of Alzheimer's disease, both in the early and late stages of the pathology. The insights gained could ultimately inform and enhance clinical practice, leading to more effective diagnostic tools and treatments.

Conclusion

Alzheimer’s disease is challenging because it often doesn't reveal itself until significant damage has been done. However, by employing advanced tools like fMRI and innovative mouse models, we're making strides in understanding and tackling this disease from both ends of the age spectrum – early and advanced stages. Our study brings hope that with continued research, we can develop strategies to diagnose Alzheimer’s early and also intervene at later stages, ensuring that patients receive effective treatments regardless of when they are identified, ultimately significantly improving the lives of millions affected by Alzheimer's.