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Living Well Study > Blog > Wellness > Innovative Model Predicts Early Signs of Alzheimer’s Disease
Wellness

Innovative Model Predicts Early Signs of Alzheimer’s Disease

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In a groundbreaking study, researchers in the laboratory of Prof. Lucía Chávez Gutiérrez at VIB-KU Leuven have made significant strides in understanding the genetic factors that contribute to familial Alzheimer’s disease (fAD). Their findings, recently published in Molecular Neurodegeneration, reveal that specific genetic mutations act as molecular clocks, precisely influencing the age at which the disease manifests. This discovery could transform early diagnostic practices and pave the way for more personalised treatment strategies for those at risk, offering hope for improved outcomes in a condition that has long defied precise prediction.

Alzheimer’s disease remains one of the most prevalent and challenging neurodegenerative disorders globally, affecting approximately 50 million people. Despite decades of intensive research, the exact mechanisms driving this devastating disease remain only partially understood. A defining feature of Alzheimer’s pathology is the formation of amyloid plaques within the brain – dense, insoluble clusters of misfolded amyloid-β (Aβ) peptide fragments. These toxic aggregates are produced through a complex molecular cascade, regulated primarily by the γ-secretase enzyme and a network of key proteins. They are believed to be critical in destroying neurons, leading to cognitive decline.

Familial Alzheimer’s disease is a rare, early-onset form of the condition that accounts for a small fraction of total Alzheimer’s cases. It is caused by inherited mutations in three critical genes: amyloid precursor protein (APP), Presenilin 1 (PSEN1), and Presenilin 2 (PSEN2). These genetic variants significantly increase the likelihood of developing Alzheimer’s at a much younger age, often decades before the more common sporadic form of the disease. However, the precise role these mutations play in driving disease onset has been a topic of intense scientific debate for decades. Understanding this link is essential for improving the accuracy of clinical diagnoses and developing targeted therapies.

“Patients with familial Alzheimer’s disease often inherit spontaneous genetic mutations, but until now, clinicians have struggled to provide precise, mutation-specific predictions regarding disease onset,” explains Prof. Lucía Chávez Gutiérrez. “Our team has developed a method to experimentally assess the likelihood of specific mutations causing the disease, along with a means to estimate the likely age of onset.” This innovative approach represents a significant breakthrough, offering a clearer understanding of how each mutation can influence the disease progression timeline.

Building on their earlier work focusing on PSEN1, the VIB-KU Leuven team has expanded their analysis to include all three significant familial Alzheimer’s genes – PSEN1, PSEN2, and APP. Their comprehensive genetic studies reveal that each of these genes contributes uniquely to the timing of disease onset, effectively functioning like ticking biological clocks. They discovered robust, gene-specific correlations between particular mutations and the age at which symptoms first appear, offering a much clearer picture of the genetic underpinnings of familial Alzheimer’s disease.

Their findings also highlight a critical link between the ratio of long-to-short Aβ peptides and the timing of disease onset. For many years, researchers have recognised that longer Aβ peptides are particularly toxic, potentially triggering the molecular pathways that lead to Alzheimer’s. This study demonstrated that even a modest, 12% shift in the Aβ peptide profile could delay the onset of familial Alzheimer’s by as much as five years, suggesting a promising therapeutic target. “This finding highlights the potential of targeting γ-secretase to alter the balance of Aβ peptides, offering a potential pathway to delay or even prevent disease onset,” notes Prof. Chávez Gutiérrez.

Beyond simply mapping genetic contributions, the research team has also developed a versatile analytical framework with dual functions. It can assess the pathogenic potential of individual genetic variants and identify patients who may carry genetic modifiers or have experienced environmental exposures that alter their expected disease onset. This approach provides a critical tool for genetic counselling and risk assessment, moving the field closer to truly personalised medicine for Alzheimer’s patients.

The researchers are optimistic that their predictive model for disease onset could transform patient care. “Our model represents a critical step toward personalised treatment strategies,” adds Sara Gutiérrez Fernández, the study’s first author. “With continued research, we aim to refine this model further, ultimately providing clinicians with more precise tools for early diagnosis and patient management.” As this line of research advances, it promises to reshape our understanding of familial Alzheimer’s disease, offering new hope to those at risk of this devastating condition.

More information: Sara Gutiérrez Fernández et al, Spectrum of γ-Secretase dysfunction as a unifying predictor of ADAD age at onset across PSEN1, PSEN2 and APP causal genes, Molecular Neurodegeneration. DOI: 10.1186/s13024-025-00832-1

Journal information: Molecular Neurodegeneration Provided by Vlaams Instituut voor Biotechnologie

TAGGED:alzheimer diseasedementianeurodegenerative diseases
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