Brain connectivity in Alzheimer’s disease: a new therapeutic target beyond amyloid?

Doctoral researcher Marta Arbizu explains how brain connectivity acts as an early biomarker in Alzheimer’s disease and why the future of neuromodulation in Alzheimer’s disease is moving toward a network-driven approach.

Beyond amyloid: advancing our understanding of Alzheimer’s disease

In recent years, pharmacological treatment of Alzheimer’s disease (AD) has made significant progress with the arrival of immunotherapies targeting amyloid-β. Some of these drugs have achieved a significant reduction in the brain’s amyloid burden.

Although it is true that many drugs have successfully cleared beta-amyloid plaques, and it is known that even when the plaques disappear the disease does not reverse, when the drug is administered at very early stages of the disease and without significant cognitive impairment, its efficacy can considerably slow the rate of decline along these neurodegenerative trajectories.

A recent article published in the journal Brain (Pini et al., 2025) proposes an innovative alternative to this dilemma: considering not only the preclinical stages of the disease to ensure drug efficacy, but also incorporating brain connectivity as a therapeutic target capable of explaining changes in molecular brain biology and affected cognition.

What do we mean by brain connectivity? A micro- and multiscale view

Brain connectivity refers to the way different regions of the brain communicate with one another, but this concept is not limited to a single level of organization.

At the microscale, connectivity reflects basic synaptic and neuronal processes: synaptic efficacy, axonal integrity, and the local dynamics of neuronal populations. Disruptions in these mechanisms, such as tau-induced synaptic loss, constitute one of the early substrates of cognitive impairment in Alzheimer’s disease.

At the macroscopic or multiscale level, these local interactions are organized into distributed brain networks that integrate multiple distant regions to support complex functions such as episodic memory, attention, and executive control. In this sense, macroscale brain connectivity acts as a bridge between the microscopic level (synapses, neurons) and the systemic level (functional and structural networks).

Multimodality and noninvasiveness: a key advantage

One of the major strengths of studying brain connectivity is that it can be assessed using noninvasive and multimodal techniques, including:

• Resting-state functional magnetic resonance imaging (fMRI), which makes it possible to study functional synchronization between brain regions.
• Diffusion techniques, which characterize the structural connectivity of white matter (DTI).
• Electroencephalography (EEG) and magnetoencephalography (MEG), which provide high-temporal-resolution information about network dynamics.

Integrating these modalities enables a more complete characterization of the human connectome, combining structural, functional, and temporal information without invasive procedures. This is especially relevant in populations where disease progression is highly dynamic, such as patients with Alzheimer’s disease.

Connectivity as an early and sensitive marker

One of the article’s strongest arguments is that alterations in brain connectivity appear at very early stages of the Alzheimer’s disease continuum, even before brain atrophy or overt cognitive impairment can be detected.

Studies of young carriers of genetic mutations associated with familial Alzheimer’s disease, as well as people with genetic risk (APOE ε4), show changes in brain networks decades before symptoms emerge. This positions functional connectivity as an especially sensitive biomarker for preclinical stages (Aponte et al., 2025).

Brain networks and the spread of pathology

The article highlights that the spatial distribution of amyloid and, especially, tau protein follows the architecture of brain networks. Regions that are more strongly connected tend to show similar patterns of pathological accumulation.

Moreover, connectivity does not change linearly (Schultz et al., 2017), since hyperconnectivity may be observed in very early stages, possibly as a compensatory mechanism. As the disease progresses and tau accumulates, progressive hypoconnectivity and network disruption emerge.

Understanding this dynamic is key to designing treatments tailored to each stage of the disease.

Accuracy and reliability of the plasma p-tau217 test for diagnosing Alzheimer’s disease

A plastic and potentially modulable phenomenon

Unlike other more static biomarkers, brain connectivity is plastic. Studies in other neurological conditions, as well as research using noninvasive brain stimulation in Alzheimer’s disease, show that networks can reorganize and partially normalize, leading to transient cognitive improvements.

This plasticity opens the door to combined therapeutic strategies, in which pharmacological treatments are complemented by interventions aimed at strengthening or stabilizing brain networks.

Toward network-driven brain stimulation

From this perspective, the future of neuromodulation in Alzheimer’s disease is moving toward a network-driven approach, in which stimulation targets are defined not solely by isolated anatomical coordinates, but by the organization and functional state of specific brain networks.

Combining brain connectivity with noninvasive stimulation would make it possible to select personalized targets, tailor the intervention to the stage of the disease, and monitor the therapeutic response at the network level, moving toward truly precision neuromodulation.

Integrating genetics, the exposome, and clinical data

Another innovative aspect is connectivity’s ability to act as a point of convergence between:

• Genetic factors (such as APOE or polygenic risk),
• Environmental factors (pollution, lifestyle),
• Biological processes (inflammation, synaptic damage).

From this perspective, Alzheimer’s disease is understood as a systems disorder, in which brain networks reflect the cumulative interaction of multiple risks over the course of life.

Can connectivity be an endpoint in clinical trials?

Currently, no pharmacological trial in Alzheimer’s disease uses brain connectivity as the primary efficacy endpoint. Nevertheless, the authors argue that it could play a key role as an intermediate endpoint, making it possible to:

• Detect therapeutic effects before clinical changes are observed.
• Improve patient stratification.
• Assess the impact of treatments on the brain’s functional organization.

Although methodological challenges remain (standardization, clinical interpretation), the accumulated evidence points to enormous translational potential.

Brain connectivity and research excellence in Spain

In this context, Spain has internationally recognized groups studying brain connectivity. One of them is the Computational Neuroimaging Lab, founded by Dr. Jesús M. Cortés, Ikerbasque professor and Director of Research at NeuronUP. This laboratory has been a pioneer in the multiscale analysis of brain connectivity and its clinical application in various neurological conditions, contributing to the development of integrative approaches that connect neuroimaging, cognition, and rehabilitation.

What implications does this approach have for NeuronUP?

At NeuronUP, we work from an integrative perspective on brain health. The proposal to use connectivity as a functional marker naturally aligns with digital cognitive assessment and rehabilitation platforms, as it makes it possible to:

• Relate changes in cognitive performance to changes in brain networks.
• Personalize interventions by considering each patient’s vulnerability and resilience.
• Complement biomedical advances with stimulation programs that harness brain plasticity.

Connectivity thus acts as a bridge between biology, cognition, and therapeutic intervention.

References

• Aponte, C., Jimenez-Marin, A., Razkin, M., Ochoa Gómez, J. F., Tobón, C., Erramuzpe, A., Diez, I., Aguillon-Niño, D., & Cortes, J. M. (2025, April 15). Subregional functional connectivity of the precuneus as a preclinical biomarker in Alzheimer’s disease (Version 1) [Preprint]. medRxiv. https://doi.org/10.1101/2025.04.15.25325852v1
• CompNeuroBilbao. (n.d.). CompNeuroBilbao (Computational Neuroimaging Lab). Retrieved December 18, 2025, from https://compneurobilbao.eus/
• Pini, L., Allali, G., Imbimbo, B. P., Germani, M., & Corbetta, M. (2025). Brain connectivity as a new target for Alzheimer’s disease therapy? Brain. Advance online publication. https://doi.org/10.1093/brain/awaf404
• Schultz, A. P., Chhatwal, J. P., Hedden, T., Mormino, E. C., Hanseeuw, B. J., Sepulcre, J., Huijbers, W., LaPoint, M., Buckley, R. F., Johnson, K. A., & Sperling, R. A. (2017). Phases of hyperconnectivity and hypoconnectivity in the default mode and salience networks track with amyloid and tau in clinically normal individuals. Journal of Neuroscience, 37(16), 4323–4331. https://doi.org/10.1523/JNEUROSCI.3263-16.2017

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