Scientists develop model to predict Alzheimer’s disease onset
Researchers from the VIB-KU Leuven Center for Brain & Disease Research have unveiled a predictive model that could revolutionise Alzheimer’s disease diagnosis and treatment strategies. Their study, published in Molecular Neurodegeneration, reveals how specific genetic mutations in three causal genes create a ‘molecular clock’ that accurately forecasts disease onset, potentially enabling clinicians to provide personalised interventions years before symptoms appear.
Genetic mutations as predictive timers for familial Alzheimer’s disease
A groundbreaking study from Belgium has established a quantitative framework for predicting the age of onset in familial Alzheimer’s disease (ADAD) based on specific genetic mutations and their effects on amyloid-beta (Aβ) protein processing.
The research team, led by Professor Lucía Chávez Gutiérrez at the VIB-KU Leuven Center for Brain & Disease Research, analysed how mutations in three causal genes – PSEN1, PSEN2, and APP – affect the production of Aβ peptides and correlate with the timing of disease onset.
“In familial Alzheimer’s disease, patients are often seen to have spontaneous genetic mutations, but until now doctors have not been able to provide patients more specific information about them,” explains Professor Lucía Chávez Gutiérrez. “We have developed a method to experimentally test how likely a mutation is to cause the disease, as well as to predict disease onset.”
Decoding the molecular mechanisms of Alzheimer’s disease development
The study follows previous research that demonstrated a strong correlation between mutations in the PSEN1 gene and the age of Alzheimer’s disease onset. The team has now expanded this analysis to include mutations in PSEN2 and APP genes, providing a comprehensive understanding of how these genetic alterations contribute to disease pathogenesis.
Using biochemical analysis, the researchers measured the effects of 28 PSEN2 and 19 APP mutations on the production and composition of Aβ peptides, particularly the ratio between shorter and longer forms of these proteins. They discovered that specific mutations alter the efficiency of gamma-secretase, an enzyme complex that processes amyloid precursor protein (APP) into Aβ peptides.
The researchers established a clear linear correlation between mutation-induced changes in Aβ profiles and the age of symptom onset. These findings support a unified model of ADAD pathogenesis where gamma-secretase dysfunction and the resulting shifts in Aβ profiles are central to disease onset across all causal genes.
Gene-specific delays in disease onset
One of the most striking findings was the identification of gene-specific “delays” in disease onset, with PSEN2 mutations showing a 27-year delay and APP mutations showing an 8-year delay compared to PSEN1 mutations.
The team demonstrated that while similar shifts in Aβ profiles occur across all three causal genes, their impact on the age of onset varies depending on the gene’s contribution to APP processing in the brain.
“The integration of PSEN1, PSEN2 and APP correlation data shows parallel but shifted lines, suggesting a common pathogenic mechanism with gene-specific shifts in onset,” explains Sara Gutiérrez Fernández, first author of the study. “We can measure the exact contribution of each gene and even predict when the first symptoms will appear.”
Implications for diagnosis and treatment
This research establishes a predictive model that could significantly improve clinical management of familial Alzheimer’s disease by enabling more accurate diagnosis and personalised treatment strategies.
“Our data predicts that a 12% shift in Aβ profile could delay the age of onset in familial Alzheimer’s disease by up to 5 years,” says Professor Lucía Chávez Gutiérrez. “This highlights the potential of therapies that target γ-secretase in the brain to create shorter forms of Aβ, and in turn delay or prevent disease onset.”
The study authors note in their paper discussion that “by linking shifts in APP/Aβ processing to symptom onset, this analysis lays the groundwork for future research focused on mechanisms modulating AAO broadly in ADAD, including those downstream of Aβ, and supports the therapeutic development of strategies that modulate Aβ generation with implications for sporadic AD.”
The findings not only enhance our understanding of the genetic mechanisms underlying familial Alzheimer’s disease but also open new avenues for developing targeted therapeutic interventions that could potentially delay or prevent disease onset in both familial and sporadic forms of Alzheimer’s disease.
Reference:
Fernández, S. G., Oria, C. G., Petit, D., et. al. (2025). Spectrum of γ-Secretase dysfunction as a unifying predictor of ADAD age at onset across PSEN1, PSEN2 and APP causal genes. Molecular Neurodegeneration, 20(48). https://doi.org/10.1186/s13024-025-00832-1
