Using artificial intelligence, researchers show how γ-secretase recognizes substrates – an important advance for fundamental and translational research.

In a Review, researchers provide a critical evaluation of research linking glymphatic dysfunction with Alzheimer’s disease. Since its discovery over a decade ago, the glymphatic system is the fluid exchange network that clears metabolic waste from the central nervous system, including harmful proteins like amyloid-beta (Aβ) and tau – and has been extensively studied in animal models and linked to various risk factors for Alzheimer’s disease (AD). However, in humans, the evidence remains largely correlative: while associations between glymphatic dysfunction and AD pathology have been observed, its causal role remains poorly understood. In this Review, Samantha Keil and colleagues provide an extensive overview of the current state of research with a focus on current approaches used to assess glymphatic function clinically. According to Keil et al., the main challenges in understanding glymphatic dysfunction’s role in human AD are due to anatomical and physiological differences between model species and humans, as well as limitations in imaging techniques used to measure glymphatic exchange in the human brain. To address this, the authors argue that the development of validated, noninvasive tools to measure glymphatic activity in humans should be a top priority in the field. Advances in neuroimaging, fluid biomarkers, and potentially wearable or device-based monitoring could enable longitudinal studies to determine whether impaired glymphatic function precedes AD pathology or cognitive decline. According to Keil et al., these advances would allow researchers to test whether enhancing glymphatic clearance – either pharmacologically, behaviorally, or technologically – could serve as a primary prevention strategy and represent a paradigm shift in AD therapeutics.

Researchers from DZNE, Ludwig-Maximilians-Universität München, and Technical University of Munich have found that the enzyme “gamma-secretase” – implicated in Alzheimer’s disease and cancer – selects its reaction partners according to a complex scheme of molecular features.

It’s been recognized for some time that Alzheimer’s disease affects brain regions differently and that tau — a protein known to misbehave — plays an important role in the disease. Brain areas like the entorhinal cortex and hippocampus succumb early to tau tangles, while other areas, like the primary sensory cortices, remain resilient to the disease. In the quest to better understand this selective vulnerability (SV) or resilience (SR) to Alzheimer’s disease, researchers have looked to gene association and transgenic studies to identify Alzheimer’s risk genes. But past research has not shown a clear link between the location of genetic risk factors and associated tau pathology. Now, a new study by UC San Francisco researchers has made a leap toward answering that question — by combining brain imaging, genetics, and advanced mathematical modeling into a powerful new lens. The study, published July 9 in Brain, shows multiple distinct pathways by which risk genes confer vulnerability or resilience in Alzheimer’s disease.

Based on the analysis of the genotypes of 500 volunteers, the research project aims to develop a panel of prognostic biomarkers and differentiate Alzheimer’s disease from other types of dementia using blood tests.