Brain connectivity as a new target for Alzheimer’s disease therapy?

The recent introduction of immunotherapeutic agents targeting amyloid-β (Aβ) has advanced the pharmacological treatment of Alzheimer's disease (AD). Although several anti-Aβ antibodies have dramatically reduced cerebral amyloid plaques, this has not translated into major cognitive or clinical benefits, thus questioning the clinical relevance of these biomarker changes. Indeed, there is an ongoing debate over whether amyloid reduction alone constitutes sufficient evidence of disease modification to justify regulatory approval. Against this backdrop, we propose a third pathway that transcends the binary framework of molecular versus clinical end points by positioning brain connectivity as a system-level intermediate phenotype. This approach is supported by a growing body of evidence. Alterations in brain networks are early, sensitive, and modifiable markers of AD pathology. Connectivity metrics capture the dynamic interplay between genetic and environmental factors, offering a unified model of disease. Advances in precision medicine, such as individualized connectivity 'fingerprints' and the emergence of digital twins, further position brain connectivity as a powerful platform for therapeutic innovation. We argue that adopting brain network analysis as a key outcome measure enables a shift beyond isolated biomarker achievements toward a more integrated, biologically grounded, and clinically meaningful framework for disease modification in AD, bridging the gap between molecular advances and real-world impact.

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Publication Details

Journal
Brain
Published
2025-10-21
DOI
https://doi.org/10.1093/brain/awaf404
Citations
2
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
2.86
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article

Brain connectivity as a new target for Alzheimer’s disease therapy?

Massimiliano Germani, Gilles Allali, Bruno Pietro Imbimbo, Lorenzo Pini et al.
2 citations
Brain
Functional Brain Connectivity Studies
2.86
article

Brain connectivity as a new target for Alzheimer’s disease therapy?

Massimiliano Germani, Gilles Allali, Bruno Pietro Imbimbo, Lorenzo Pini, Maurizio Corbetta
article en
2 citations

Abstract

The recent introduction of immunotherapeutic agents targeting amyloid-β (Aβ) has advanced the pharmacological treatment of Alzheimer's disease (AD). Although several anti-Aβ antibodies have dramatically reduced cerebral amyloid plaques, this has not translated into major cognitive or clinical benefits, thus questioning the clinical relevance of these biomarker changes. Indeed, there is an ongoing debate over whether amyloid reduction alone constitutes sufficient evidence of disease modification to justify regulatory approval. Against this backdrop, we propose a third pathway that transcends the binary framework of molecular versus clinical end points by positioning brain connectivity as a system-level intermediate phenotype. This approach is supported by a growing body of evidence. Alterations in brain networks are early, sensitive, and modifiable markers of AD pathology. Connectivity metrics capture the dynamic interplay between genetic and environmental factors, offering a unified model of disease. Advances in precision medicine, such as individualized connectivity 'fingerprints' and the emergence of digital twins, further position brain connectivity as a powerful platform for therapeutic innovation. We argue that adopting brain network analysis as a key outcome measure enables a shift beyond isolated biomarker achievements toward a more integrated, biologically grounded, and clinically meaningful framework for disease modification in AD, bridging the gap between molecular advances and real-world impact.

BrainVol. 149(2)
University of Padua (IT), Veneto Institute of Molecular Medicine (IT), Chiesi Foundation (IT), Chiesi (France) (FR), University of Lausanne (CH)
Openalex Percentile: Top 8%
Functional Brain Connectivity Studies
2.86
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Brain connectivity as a new target for Alzheimer’s disease therapy? — Massimiliano Germani, Gilles Allali, et al. · Brain (2025) | TGRS Research Map | TGRS